R Under development (unstable) (2024-08-15 r87022 ucrt) -- "Unsuffered Consequences"
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> commandArgs()
[1] "D:\\RCompile\\recent\\R/bin/x64/Rterm.exe"
[2] "-f"                                       
[3] "nlrob-tst.R"                              
[4] "--restore"                                
[5] "--save"                                   
[6] "--vanilla"                                
> library(robustbase)
> 
> ## for now: ----------------------------------------
> if(file.exists(fil <- system.file("xtraR/test-tools.R",  package = "robustbase"))) {
+     source(fil)
+ } else {
+   identical3 <- function(x,y,z)	  identical(x,y) && identical (y,z)
+   identical4 <- function(a,b,c,d)   identical(a,b) && identical3(b,c,d)
+   assert.EQ <- function(target, current, tol = if(showOnly) 0 else 1e-15,
+                       giveRE = FALSE, showOnly = FALSE, ...) {
+     ## Purpose: check equality *and* show non-equality
+     ## ----------------------------------------------------------------------
+     ## showOnly: if TRUE, return (and hence typically print) all.equal(...)
+     T <- isTRUE(ae <- all.equal(target, current, tolerance = tol, ...))
+     if(showOnly) return(ae) else if(giveRE && T) { ## don't show if stop() later:
+ 	ae0 <- if(tol == 0) ae else all.equal(target, current, tolerance = 0, ...)
+ 	if(!isTRUE(ae0)) writeLines(ae0)
+     }
+     if(!T) stop("all.equal() |-> ", paste(ae, collapse=sprintf("%-19s","\n")))
+     else if(giveRE) invisible(ae0)
+   }
+ }
> if(FALSE) ## in future: ----------------------------------------
+ source(system.file("xtraR/test-tools.R",  package = "robustbase"))
> ##
> ## -> assert.EQ(), identical3(), ..
> 
> 
> ## From  <Rsrc>/tests/reg-tests-1d.R  (2022-08-09):
> ## A good guess if we have _not_ translated error/warning/.. messages:
> ## (should something like this be part of package tools ?)
> englishMsgs <- {
+     ## 1. LANGUAGE takes precedence over locale settings:
+     if(nzchar(lang <- Sys.getenv("LANGUAGE")))
+         lang == "en"
+     else { ## 2. Query the  locale
+         if(!onWindows) {
+             ## sub() :
+             lc.msgs <- sub("\\..*", "", print(Sys.getlocale("LC_MESSAGES")))
+             lc.msgs == "C" || substr(lc.msgs, 1,2) == "en"
+         } else { ## Windows
+             lc.type <- sub("\\..*", "", sub("_.*", "", print(Sys.getlocale("LC_CTYPE"))))
+             lc.type == "English" || lc.type == "C"
+         }
+     }
+ }
> cat(sprintf("English messages: %s\n", englishMsgs))
English messages: FALSE
> 
> 
> DNase1 <- DNase[ DNase$Run == 1, ]
> Y <- DNase1[,"density"] # for convenience below
> 
> ## classical
> fm1 <- nls(density ~ Asym/(1 + exp(( xmid - log(conc) )/scal ) ),
+ 	   data = DNase1, start = list(Asym = 3, xmid = 0, scal = 1), trace=TRUE)
14.32279    (3.02e+01): par = (3 0 1)
0.4542698   (9.73e+00): par = (2.115246 0.8410193 1.200064)
0.05869603  (3.34e+00): par = (2.446376 1.747516 1.189515)
0.005663524 (4.26e-01): par = (2.294087 1.412198 1.020463)
0.004791528 (2.02e-02): par = (2.341429 1.479688 1.040758)
0.004789569 (1.65e-04): par = (2.345135 1.483047 1.041439)
0.004789569 (1.94e-06): par = (2.345179 1.483089 1.041454)
> summary(fm1)

Formula: density ~ Asym/(1 + exp((xmid - log(conc))/scal))

Parameters:
     Estimate Std. Error t value Pr(>|t|)    
Asym  2.34518    0.07815   30.01 2.17e-13 ***
xmid  1.48309    0.08135   18.23 1.22e-10 ***
scal  1.04145    0.03227   32.27 8.51e-14 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.01919 on 13 degrees of freedom

Number of iterations to convergence: 6 
Achieved convergence tolerance: 1.937e-06

> wm1 <- update(fm1, weights = sqrt(conc)) # (weights as function of <var>)
27.10073    (3.68e+01): par = (3 0 1)
0.6008020   (8.66e+00): par = (2.182337 0.8948353 1.261465)
0.1716286   (4.40e+00): par = (2.51089 1.828486 1.208884)
0.01052871  (5.11e-01): par = (2.282185 1.401035 1.024226)
0.008359719 (6.68e-02): par = (2.359573 1.499564 1.050668)
0.008322484 (7.54e-04): par = (2.367424 1.506046 1.052066)
0.008322479 (1.51e-05): par = (2.367618 1.506233 1.052148)
0.008322479 (3.04e-07): par = (2.367622 1.506237 1.05215)
> 
> ## robust
> rm1 <- nlrob(formula(fm1), data = DNase1, trace = TRUE,
+ 	     start = list(Asym = 3, xmid = 0, scal = 1))
robust iteration 1 
14.32279    (3.02e+01): par = (3 0 1)
0.4542698   (9.73e+00): par = (2.115246 0.8410193 1.200064)
0.05869603  (3.34e+00): par = (2.446376 1.747516 1.189515)
0.005663524 (4.26e-01): par = (2.294087 1.412198 1.020463)
0.004791528 (2.02e-02): par = (2.341429 1.479688 1.040758)
0.004789569 (1.65e-04): par = (2.345135 1.483047 1.041439)
0.004789569 (1.94e-06): par = (2.345179 1.483089 1.041454)
 --> irls.delta(previous, resid) = 0.999803 -- *not* converged
robust iteration 2 
0.003971483 (6.54e-02): par = (2.345179 1.483089 1.041454)
0.003954569 (1.07e-03): par = (2.356445 1.495544 1.043788)
0.003954564 (2.75e-06): par = (2.356586 1.49565 1.043815)
 --> irls.delta(previous, resid) = 0.0614627 -- *not* converged
robust iteration 3 
0.003934724 (1.25e-02): par = (2.356586 1.49565 1.043815)
0.003934110 (8.81e-05): par = (2.358633 1.498205 1.044647)
0.003934110 (7.29e-07): par = (2.358657 1.498229 1.044655)
 --> irls.delta(previous, resid) = 0.0121516 -- *not* converged
robust iteration 4 
0.003930685 (4.06e-03): par = (2.358657 1.498229 1.044655)
0.003930620 (2.54e-05): par = (2.359307 1.499046 1.044928)
0.003930620 (2.43e-07): par = (2.359314 1.499053 1.044931)
 --> irls.delta(previous, resid) = 0.00395055 -- *not* converged
robust iteration 5 
0.003929580 (1.33e-03): par = (2.359314 1.499053 1.044931)
0.003929573 (8.09e-06): par = (2.359525 1.49932 1.04502)
 --> irls.delta(previous, resid) = 0.00128456 -- *not* converged
robust iteration 6 
0.003929244 (4.37e-04): par = (2.359525 1.49932 1.04502)
0.003929244 (2.65e-06): par = (2.359596 1.499409 1.04505)
 --> irls.delta(previous, resid) = 0.000423026 -- *not* converged
robust iteration 7 
0.003929132 (1.44e-04): par = (2.359596 1.499409 1.04505)
0.003929132 (8.44e-07): par = (2.35962 1.499438 1.04506)
 --> irls.delta(previous, resid) = 0.000139333 -- *not* converged
robust iteration 8 
0.003929095 (4.73e-05): par = (2.35962 1.499438 1.04506)
0.003929095 (3.19e-07): par = (2.359628 1.499448 1.045063)
 --> irls.delta(previous, resid) = 4.58704e-05 -- *not* converged
robust iteration 9 
0.003929083 (1.56e-05): par = (2.359628 1.499448 1.045063)
0.003929083 (1.13e-07): par = (2.35963 1.499451 1.045064)
 --> irls.delta(previous, resid) = 1.51307e-05 -- *not* converged
robust iteration 10 
0.003929079 (5.16e-06): par = (2.35963 1.499451 1.045064)
> (sm1 <- summary(rm1))

Call:
nlrob(formula = formula(fm1), data = DNase1, start = list(Asym = 3, 
    xmid = 0, scal = 1), trace = TRUE, algorithm = "default")

Residuals:
       Min         1Q     Median         3Q        Max 
-0.0322811 -0.0130976 -0.0008932  0.0095784  0.0404174 

Parameters:
     Estimate Std. Error t value Pr(>|t|)    
Asym  2.35963    0.08627   27.35 7.10e-13 ***
xmid  1.49945    0.09022   16.62 3.87e-10 ***
scal  1.04506    0.03504   29.83 2.34e-13 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Robust residual standard error: 0.01829 
Convergence in 10 IRWLS iterations

Robustness weights: 
 14 weights are ~= 1. The remaining 2 ones are
    11     13 
0.6087 0.7621 
> stopifnot(all.equal(Y, fitted(fm1) + residuals(fm1), check.attributes=FALSE),
+ 	  ## fitted(<nls>) has "label" attribute
+ 	  identical3(c(fitted(fm1)), predict(fm1), predict(fm1, newdata=DNase1)),
+ 	  ## robust fit :
+ 	  identical3(fitted(rm1), predict(rm1), predict(rm1, newdata=DNase1)),
+ 	  all.equal(Y, unname(fitted(rm1) + residuals(rm1))))
> print(coef(rm1), digits=12)
         Asym          xmid          scal 
2.35963009745 1.49945089781 1.04506392233 
> ## 2.35963008460 1.49945088410 1.04506391722	F19 Lx 64b
> ## 2.35963008460 1.49945088410 1.04506391722	Win(Serv.2003) 64b
> ## 2.35963008613 1.49945088600 1.04506391793	F19 Lx 32b
> ## 2.35963008613 1.49945088600 1.04506391793	Win(Serv.2003) 32b
> assert.EQ(coef(rm1), giveRE=TRUE,
+ 	  c(Asym=2.35963008, xmid=1.49945088, scal=1.04506392), tol = 4e-8)
Mean relative difference: 7.665855e-09
> assert.EQ(sqrt(diag(sm1$cov)), giveRE=TRUE,
+ 	  ## 32b 0.08626872273,     0.0902194541,      0.03503833759
+ 	  c(Asym=0.0862687305, xmid=0.0902194608, scal=0.0350383389),
+ 	  tol = 7e-7)
Mean relative difference: 1.147459e-07
> ## examples with weights:
> rm. <- update(rm1, weights = NULL)# 'NULL' but not missing()
robust iteration 1 
14.32279    (3.02e+01): par = (3 0 1)
0.4542698   (9.73e+00): par = (2.115246 0.8410193 1.200064)
0.05869603  (3.34e+00): par = (2.446376 1.747516 1.189515)
0.005663524 (4.26e-01): par = (2.294087 1.412198 1.020463)
0.004791528 (2.02e-02): par = (2.341429 1.479688 1.040758)
0.004789569 (1.65e-04): par = (2.345135 1.483047 1.041439)
0.004789569 (1.94e-06): par = (2.345179 1.483089 1.041454)
 --> irls.delta(previous, resid) = 0.999803 -- *not* converged
robust iteration 2 
0.003971483 (6.54e-02): par = (2.345179 1.483089 1.041454)
0.003954569 (1.07e-03): par = (2.356445 1.495544 1.043788)
0.003954564 (2.75e-06): par = (2.356586 1.49565 1.043815)
 --> irls.delta(previous, resid) = 0.0614627 -- *not* converged
robust iteration 3 
0.003934724 (1.25e-02): par = (2.356586 1.49565 1.043815)
0.003934110 (8.81e-05): par = (2.358633 1.498205 1.044647)
0.003934110 (7.29e-07): par = (2.358657 1.498229 1.044655)
 --> irls.delta(previous, resid) = 0.0121516 -- *not* converged
robust iteration 4 
0.003930685 (4.06e-03): par = (2.358657 1.498229 1.044655)
0.003930620 (2.54e-05): par = (2.359307 1.499046 1.044928)
0.003930620 (2.43e-07): par = (2.359314 1.499053 1.044931)
 --> irls.delta(previous, resid) = 0.00395055 -- *not* converged
robust iteration 5 
0.003929580 (1.33e-03): par = (2.359314 1.499053 1.044931)
0.003929573 (8.09e-06): par = (2.359525 1.49932 1.04502)
 --> irls.delta(previous, resid) = 0.00128456 -- *not* converged
robust iteration 6 
0.003929244 (4.37e-04): par = (2.359525 1.49932 1.04502)
0.003929244 (2.65e-06): par = (2.359596 1.499409 1.04505)
 --> irls.delta(previous, resid) = 0.000423026 -- *not* converged
robust iteration 7 
0.003929132 (1.44e-04): par = (2.359596 1.499409 1.04505)
0.003929132 (8.44e-07): par = (2.35962 1.499438 1.04506)
 --> irls.delta(previous, resid) = 0.000139333 -- *not* converged
robust iteration 8 
0.003929095 (4.73e-05): par = (2.35962 1.499438 1.04506)
0.003929095 (3.19e-07): par = (2.359628 1.499448 1.045063)
 --> irls.delta(previous, resid) = 4.58704e-05 -- *not* converged
robust iteration 9 
0.003929083 (1.56e-05): par = (2.359628 1.499448 1.045063)
0.003929083 (1.13e-07): par = (2.35963 1.499451 1.045064)
 --> irls.delta(previous, resid) = 1.51307e-05 -- *not* converged
robust iteration 10 
0.003929079 (5.16e-06): par = (2.35963 1.499451 1.045064)
> ww <- sqrt(DNase1[,"conc"])
> wr1  <- update(rm1, weights = sqrt(conc), trace=FALSE)
> wr1. <- update(rm1, weights = ww,         trace=FALSE)
> ii <- names(rm1) != "call"
> stopifnot(all.equal(rm1[ii], rm.[ii], tol = 1e-15),
+           all.equal(wr1[ii],wr1.[ii], tol = 1e-15))
> 
> ## When y has NA's: Add them to the end of DNase1
> n <- nrow(DNase1)
> DNAnase <- DNase1[c(1:n,1:3), ]
> DNAnase$density[n+(1:3)] <- NA
> 
> naExp <- expression(na.fail = na.fail, # << the default in model.frame() which most use
+                     na.omit = na.omit,
+                     na.pass = na.pass,
+                     na.exclude= na.exclude)
> 
> noAction <- function(fm) {
+     if(("call" %in% names(fm)) && !is.null(fm$call))
+         fm$call <- noAction(fm$call)
+     if(!is.na(H <- match("na.action", names(fm))))
+         fm[-H]
+     else
+         fm
+ }
> 
> rNls <- lapply(naExp, function(naAct)
+     tryCatch(error = identity,
+        nls(formula(fm1), data = DNAnase,
+            na.action = eval(naAct),
+            start = list(Asym = 3, xmid = 0, scal = 1))
+        )
+     )
> 
> str(sapply(rNls, class))
List of 4
 $ na.fail   : chr [1:3] "simpleError" "error" "condition"
 $ na.omit   : chr "nls"
 $ na.pass   : chr [1:3] "simpleError" "error" "condition"
 $ na.exclude: chr "nls"
> ## $ na.fail   : chr [1:3] "simpleError" "error" "condition"
> ## $ na.omit   : chr "nls"
> ## $ na.pass   : chr [1:3] "simpleError" "error" "condition"
> ## $ na.exclude: chr "nls"
> 
> stopifnot(exprs = {
+     inherits(rNls$na.pass, "simpleError")
+     inherits(rNls$na.fail, "simpleError")
+ })
> 
> if(englishMsgs) stopifnot(exprs = {
+     conditionMessage(rNls$na.fail) == "missing values in object"
+     grepl("NA.*foreign function call", conditionMessage(rNls$na.pass))
+ })
> 
> sO <- summary(rNls$na.omit)
> sX <- summary(rNls$na.exclude)
> stopifnot(exprs = {
+     identical(noAction(sO),
+               noAction(sX))
+     all.equal(coef(sm1), coef(sX), tol = 0.10) # 0.0857
+ })
> 
> 
> robNls <- lapply(c(noCov=FALSE,doCov=TRUE), function(doCov)
+     lapply(naExp, function(naAct)
+         tryCatch(error = identity,
+                  nlrob(formula(fm1), data = DNAnase,
+                        na.action = eval(naAct),
+                        doCov = doCov, ## <--
+                        start = list(Asym = 3, xmid = 0, scal = 1))
+                  )
+         )
+     )
Warning messages:
1: In old - new :
  longer object length is not a multiple of shorter object length
2: In old - new :
  longer object length is not a multiple of shorter object length
> ## gives
> ## Warning messages:
> ## In old - new :
> ##   longer object length is not a multiple of shorter object length
> 
> str(sapply(robNls[["noCov"]], class))
List of 4
 $ na.fail   : chr [1:3] "simpleError" "error" "condition"
 $ na.omit   : chr [1:3] "simpleError" "error" "condition"
 $ na.pass   : chr [1:3] "simpleError" "error" "condition"
 $ na.exclude: chr [1:2] "nlrob" "nls"
> ## List of 4
> ##  $ na.fail   : chr [1:3] "simpleError" "error" "condition"
> ##  $ na.omit   : chr [1:3] "simpleError" "error" "condition"  <<< FIXME, should work as nls() does
> ##  $ na.pass   : chr [1:3] "simpleError" "error" "condition"
> ##  $ na.exclude: chr [1:2] "nlrob" "nls"
> stopifnot(identical(sapply(robNls[["noCov"]], class),
+                     sapply(robNls[["doCov"]], class)))
> 
> ## same checks as for nls():
> lapply(robNls, function(LL)
+     stopifnot(exprs = {
+         inherits(LL$na.pass, "simpleError")
+         inherits(LL$na.fail, "simpleError")
+     })) -> .tmp
> 
> if(englishMsgs) lapply(robNls, function(LL)
+     stopifnot(exprs = {
+         conditionMessage(LL$na.fail) == "missing values in object"
+         ## different message than nls():
+         grepl("missing.*weights not allowed", conditionMessage(LL$na.pass))
+     })
+     ) -> .tmp
> 
> ## the only one which works currently:
> robNxcl <- robNls[["noCov"]]$na.exclude
> 
> ## Fix these : ===================
> .t <- try( s.no <- summary(robNxcl) )
Error in .vcov.m(object, Scale = sc, resid.sc = as.vector(object$residuals)/sc) : 
  length(resid.sc) == nobs(object) is not TRUE
> .t <- try( v.no <- vcov(robNxcl) )
Error in .vcov.m(object, Scale = sc, resid.sc = as.vector(object$residuals)/sc) : 
  length(resid.sc) == nobs(object) is not TRUE
> ## both give *same* error:
> ## Error in .vcov.m(object, Scale = sc, resid.sc = as.vector(object$residuals)/sc) :
> ##   length(resid.sc) == nobs(object) is not TRUE
> 
> 
> 
> ## Fix these : ===================
> str( s.do <- summary(robNls[["doCov"]]$na.exclude) )
List of 12
 $ formula     :Class 'formula'  language density ~ Asym/(1 + exp((xmid - log(conc))/scal))
  .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
 $ residuals   : Named num [1:19] -0.01385 -0.01285 0.00883 0.01183 -0.00241 ...
  ..- attr(*, "names")= chr [1:19] "1" "2" "3" "4" ...
 $ Scale       : num 0.0183
 $ w           : num [1:19] 1 1 1 1 1 1 1 1 1 1 ...
 $ rweights    : num [1:19] 1 1 1 1 1 1 1 1 1 1 ...
 $ cov         : num [1:3, 1:3] NA NA NA NA NA NA NA NA NA
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "Asym" "xmid" "scal"
  .. ..$ : chr [1:3] "Asym" "xmid" "scal"
 $ call        : language nlrob(formula = formula(fm1), data = DNAnase, start = list(Asym = 3, xmid = 0,      scal = 1), na.action = eval(n| __truncated__
 $ status      : chr "converged"
 $ iter        : int 10
 $ control     :List of 7
  ..$ maxiter    : num 50
  ..$ tol        : num 1e-05
  ..$ minFactor  : num 0.000977
  ..$ printEval  : logi FALSE
  ..$ warnOnly   : logi FALSE
  ..$ scaleOffset: num 0
  ..$ nDcentral  : logi FALSE
 $ df          : int [1:2] 3 NA
 $ coefficients: num [1:3, 1:4] 2.36 1.5 1.05 NA NA ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "Asym" "xmid" "scal"
  .. ..$ : chr [1:4] "Estimate" "Std. Error" "t value" "Pr(>|t|)"
 - attr(*, "class")= chr "summary.nlrob"
> 
> try(## the "doCov" -- fails "only" when printing:
+     print(s.do) #-> error
+ ) -> .tmp

Call:
nlrob(formula = formula(fm1), data = DNAnase, start = list(Asym = 3, 
    xmid = 0, scal = 1), na.action = eval(naAct), doCov = doCov, 
    algorithm = "default")

Residuals:
Error in if (rdf > 5L) { : missing value where TRUE/FALSE needed
> ## Call:
> ## ....
> ## Residuals:
> ## Error in if (rdf > 5L) { : missing value where TRUE/FALSE needed
> 
> vcov(robNls[["doCov"]]$na.exclude)
     Asym xmid scal
Asym   NA   NA   NA
xmid   NA   NA   NA
scal   NA   NA   NA
> ##      Asym xmid scal
> ## Asym   NA   NA   NA
> ## xmid   NA   NA   NA
> ## scal   NA   NA   NA
> 
> 
> 
> try( ## debug this one
+ rmNAo <- nlrob(formula(fm1), data = DNAnase,
+                na.action = na.omit,
+                trace = TRUE,
+                start = list(Asym = 3, xmid = 0, scal = 1)) ### fails
+ ## Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE,  :
+ ##   arguments imply differing number of rows: 19, 16
+ )
robust iteration 1 
14.32279    (3.02e+01): par = (3 0 1)
0.4542698   (9.73e+00): par = (2.115246 0.8410193 1.200064)
0.05869603  (3.34e+00): par = (2.446376 1.747516 1.189515)
0.005663524 (4.26e-01): par = (2.294087 1.412198 1.020463)
0.004791528 (2.02e-02): par = (2.341429 1.479688 1.040758)
0.004789569 (1.65e-04): par = (2.345135 1.483047 1.041439)
0.004789569 (1.94e-06): par = (2.345179 1.483089 1.041454)
 --> irls.delta(previous, resid) = 0.999803 -- *not* converged
robust iteration 2 
Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE,  : 
  arguments imply differing number of rows: 19, 16
In addition: Warning message:
In old - new :
  longer object length is not a multiple of shorter object length
> 
> 
> ## From: "Pascal A. Niklaus" <pascal.niklaus@ieu.uzh.ch>
> ## To: <maechler@stat.math.ethz.ch>
> ## Subject: nlrob problem
> ## Date: Tue, 20 Dec 2011 07:04:38 +0100
> 
> ## For psi-functions that can become zero (e.g. psi.bisquare), weights in
> ## the internal call to nls can become zero.
> 
> 
> ## Was
> ## psiTuk  <- robustbase:::psi.bisquare
> ## psiHamp <- robustbase:::psi.hampel
> 
> lmrob.control(psi="bisquare")$tuning.psi
[1] 4.685061
> psiTuk <- function(x, der=0) {
+     ## cc:  dput( lmrob.control(psi="bisquare")$tuning.psi )
+     if(der == 0)
+         Mwgt(x, cc=4.685061, psi="Tukey")
+     else
+         Mpsi(x, cc=4.685061, psi="Tukey", deriv=1)
+ }
> 
> c.Ha <- lmrob.control(psi="hampel"); c.Ha$tuning.psi
[1] 1.352413 3.155630 7.212868
> psiHamp <- function(x, der=0) {
+     ## cc: dput( lmrob.control(psi="hampel")$tuning.psi )
+     if(der == 0)
+ 	Mwgt(x, cc=c(1.35241275, 3.15562975, 7.212868), psi="Hampel")
+     else
+ 	Mpsi(x, cc=c(1.35241275, 3.15562975, 7.212868), psi="Hampel", deriv=1)
+ }
> 
> d <- data.frame(x = -6:9,
+                 y = 43 + c(7, 52, 21, 12, 10, -4, -5, -4, 0, -77, -8, -10, 22, 33, 38, 51))
> nlr1 <- nlrob(y ~ a*(x + b*exp(-c*x)), start=list(a= 4, b= 1, c= 1.2),
+               data = d,
+               maxit = 50, # default 20 is *not* sufficient
+               model = TRUE,
+               trace=TRUE)
robust iteration 1 
647679.7    (7.29e+00): par = (4 1 1.2)
189112.5    (4.24e+00): par = (9.195522 -0.399165 1.050113)
98995.28    (2.69e+00): par = (9.285753 0.1707392 1.203139)
16121.01    (1.09e+00): par = (9.191364 0.3840144 0.8301526)
12197.17    (9.91e-01): par = (9.350024 1.002984 0.4775526)
10178.30    (7.56e-01): par = (9.139317 2.245923 0.2603096)
8164.592    (5.29e-01): par = (9.193081 3.049004 0.4206007)
6638.982    (7.81e-02): par = (8.781494 3.670834 0.3072424)
6611.493    (2.86e-02): par = (8.841148 3.353259 0.331349)
6608.502    (1.31e-02): par = (8.75829 3.483123 0.3206617)
6607.890    (6.06e-03): par = (8.788465 3.430109 0.3256271)
6607.759    (2.81e-03): par = (8.773229 3.456008 0.3233241)
6607.731    (1.30e-03): par = (8.780026 3.444232 0.3243899)
6607.725    (6.02e-04): par = (8.776823 3.449736 0.3238964)
6607.724    (2.78e-04): par = (8.778294 3.447198 0.3241249)
6607.724    (1.29e-04): par = (8.77761 3.448375 0.3240191)
6607.724    (5.97e-05): par = (8.777926 3.447831 0.3240681)
6607.724    (2.76e-05): par = (8.77778 3.448083 0.3240454)
6607.724    (1.28e-05): par = (8.777848 3.447966 0.3240559)
6607.724    (5.90e-06): par = (8.777816 3.44802 0.324051)
 --> irls.delta(previous, resid) = 0.980105 -- *not* converged
robust iteration 2 
5340.496    (7.42e-01): par = (8.777816 3.44802 0.324051)
3676.395    (1.25e-01): par = (8.752698 4.401561 0.232443)
3626.766    (1.99e-02): par = (8.73204 4.209926 0.2480097)
3625.628    (4.22e-03): par = (8.675651 4.285008 0.2446748)
3625.577    (8.89e-04): par = (8.6848 4.270785 0.2453872)
3625.575    (1.89e-04): par = (8.682719 4.274011 0.2452358)
3625.575    (4.02e-05): par = (8.683156 4.273332 0.245268)
3625.575    (8.54e-06): par = (8.683062 4.273477 0.2452612)
 --> irls.delta(previous, resid) = 0.436553 -- *not* converged
robust iteration 3 
3071.609    (1.20e-01): par = (8.683062 4.273477 0.2452612)
3033.045    (1.92e-02): par = (8.7166 4.463766 0.2310233)
3032.134    (3.72e-03): par = (8.749027 4.405916 0.2338778)
3032.100    (7.33e-04): par = (8.740244 4.418859 0.2333154)
3032.099    (1.45e-04): par = (8.741878 4.416415 0.2334265)
3032.099    (2.85e-05): par = (8.741552 4.416903 0.2334046)
3032.099    (5.62e-06): par = (8.741616 4.416807 0.2334089)
 --> irls.delta(previous, resid) = 0.074586 -- *not* converged
robust iteration 4 
2591.692    (5.37e-02): par = (8.741616 4.416807 0.2334089)
2584.457    (4.14e-03): par = (8.842378 4.431044 0.2302787)
2584.421    (7.56e-04): par = (8.850398 4.418702 0.2308676)
2584.420    (1.39e-04): par = (8.848781 4.421063 0.2307598)
2584.420    (2.54e-05): par = (8.849073 4.420635 0.2307795)
2584.420    (4.64e-06): par = (8.84902 4.420713 0.2307759)
 --> irls.delta(previous, resid) = 0.0291833 -- *not* converged
robust iteration 5 
2173.948    (4.47e-02): par = (8.84902 4.420713 0.2307759)
2169.635    (1.44e-03): par = (8.952107 4.407064 0.2296879)
2169.631    (2.41e-04): par = (8.95474 4.403385 0.2298785)
2169.631    (4.09e-05): par = (8.954267 4.404065 0.2298461)
2169.631    (6.95e-06): par = (8.954347 4.40395 0.2298516)
 --> irls.delta(previous, resid) = 0.0217691 -- *not* converged
robust iteration 6 
1847.900    (3.72e-02): par = (8.954347 4.40395 0.2298516)
1845.344    (2.28e-04): par = (9.043233 4.382982 0.2299199)
1845.344    (1.38e-05): par = (9.043079 4.383407 0.2299088)
1845.344    (2.19e-06): par = (9.043104 4.383371 0.2299105)
 --> irls.delta(previous, resid) = 0.0169571 -- *not* converged
robust iteration 7 
1674.072    (2.17e-02): par = (9.043104 4.383371 0.2299105)
1673.299    (1.19e-03): par = (9.101377 4.355638 0.2308565)
1673.297    (1.77e-04): par = (9.099332 4.358667 0.2307111)
1673.297    (2.67e-05): par = (9.099638 4.358233 0.230733)
1673.297    (4.03e-06): par = (9.099592 4.358299 0.2307297)
 --> irls.delta(previous, resid) = 0.0101474 -- *not* converged
robust iteration 8 
1583.914    (1.33e-02): par = (9.099592 4.358299 0.2307297)
1583.649    (1.21e-03): par = (9.134973 4.335652 0.2317212)
1583.647    (1.76e-04): par = (9.132912 4.338609 0.2315746)
1583.647    (2.58e-05): par = (9.133209 4.338189 0.231596)
1583.647    (3.77e-06): par = (9.133165 4.338251 0.2315929)
 --> irls.delta(previous, resid) = 0.00676311 -- *not* converged
robust iteration 9 
1538.119    (8.45e-03): par = (9.133165 4.338251 0.2315929)
1538.018    (8.86e-04): par = (9.153333 4.323712 0.2323299)
1538.017    (1.27e-04): par = (9.151849 4.325821 0.2322233)
1538.017    (1.83e-05): par = (9.152059 4.325523 0.2322386)
1538.017    (2.63e-06): par = (9.152029 4.325566 0.2322364)
 --> irls.delta(previous, resid) = 0.0046438 -- *not* converged
robust iteration 10 
1512.600    (5.67e-03): par = (9.152029 4.325566 0.2322364)
1512.556    (6.15e-04): par = (9.164222 4.316236 0.2327531)
1512.555    (8.73e-05): par = (9.163203 4.31768 0.2326794)
1512.555    (1.24e-05): par = (9.163347 4.317477 0.2326899)
1512.555    (1.76e-06): par = (9.163326 4.317506 0.2326884)
 --> irls.delta(previous, resid) = 0.00324717 -- *not* converged
robust iteration 11 
1496.839    (3.92e-03): par = (9.163326 4.317506 0.2326884)
1496.818    (4.27e-04): par = (9.171219 4.311296 0.2330487)
1496.818    (6.00e-05): par = (9.170519 4.312288 0.2329978)
1496.818    (8.47e-06): par = (9.170617 4.312149 0.233005)
 --> irls.delta(previous, resid) = 0.0022863 -- *not* converged
robust iteration 12 
1486.420    (2.74e-03): par = (9.170617 4.312149 0.233005)
1486.410    (2.96e-04): par = (9.175943 4.307916 0.2332563)
1486.409    (4.15e-05): par = (9.17546 4.308601 0.2332211)
1486.409    (5.80e-06): par = (9.175527 4.308506 0.233226)
 --> irls.delta(previous, resid) = 0.00160615 -- *not* converged
robust iteration 13 
1479.278    (1.92e-03): par = (9.175527 4.308506 0.233226)
1479.273    (2.07e-04): par = (9.179211 4.305566 0.2334022)
1479.273    (2.89e-05): par = (9.178874 4.306043 0.2333776)
1479.273    (4.02e-06): par = (9.178921 4.305977 0.233381)
 --> irls.delta(previous, resid) = 0.00112928 -- *not* converged
robust iteration 14 
1474.308    (1.35e-03): par = (9.178921 4.305977 0.233381)
1474.305    (1.45e-04): par = (9.181494 4.303921 0.2335047)
1474.305    (2.02e-05): par = (9.181259 4.304255 0.2334875)
1474.305    (2.80e-06): par = (9.181291 4.304208 0.2334899)
 --> irls.delta(previous, resid) = 0.000794066 -- *not* converged
robust iteration 15 
1470.829    (9.50e-04): par = (9.181291 4.304208 0.2334899)
1470.828    (1.02e-04): par = (9.183095 4.302766 0.2335769)
1470.828    (1.41e-05): par = (9.18293 4.303 0.2335648)
1470.828    (1.95e-06): par = (9.182953 4.302967 0.2335665)
 --> irls.delta(previous, resid) = 0.000558308 -- *not* converged
robust iteration 16 
1468.388    (6.68e-04): par = (9.182953 4.302967 0.2335665)
1468.388    (7.15e-05): par = (9.18422 4.301955 0.2336276)
1468.388    (9.90e-06): par = (9.184104 4.302118 0.2336191)
 --> irls.delta(previous, resid) = 0.00038736 -- *not* converged
robust iteration 17 
1466.670    (4.75e-04): par = (9.184104 4.302118 0.2336191)
1466.670    (5.13e-05): par = (9.185009 4.301387 0.2336629)
1466.670    (7.10e-06): par = (9.184926 4.301504 0.2336568)
 --> irls.delta(previous, resid) = 0.000274692 -- *not* converged
robust iteration 18 
1465.470    (3.35e-04): par = (9.184926 4.301504 0.2336568)
1465.469    (3.63e-05): par = (9.185562 4.300988 0.2336879)
1465.469    (5.01e-06): par = (9.185503 4.301071 0.2336836)
 --> irls.delta(previous, resid) = 0.000194037 -- *not* converged
robust iteration 19 
1464.629    (2.36e-04): par = (9.185503 4.301071 0.2336836)
1464.629    (2.56e-05): par = (9.18595 4.300707 0.2337055)
1464.629    (3.53e-06): par = (9.185909 4.300765 0.2337024)
 --> irls.delta(previous, resid) = 0.000136925 -- *not* converged
robust iteration 20 
1464.038    (1.67e-04): par = (9.185909 4.300765 0.2337024)
1464.038    (1.80e-05): par = (9.186224 4.300509 0.2337179)
1464.038    (2.50e-06): par = (9.186195 4.30055 0.2337157)
 --> irls.delta(previous, resid) = 9.65917e-05 -- *not* converged
robust iteration 21 
1463.621    (1.18e-04): par = (9.186195 4.30055 0.2337157)
1463.621    (1.27e-05): par = (9.186416 4.300369 0.2337266)
1463.621    (1.76e-06): par = (9.186396 4.300398 0.2337251)
 --> irls.delta(previous, resid) = 6.8134e-05 -- *not* converged
robust iteration 22 
1463.328    (8.29e-05): par = (9.186396 4.300398 0.2337251)
1463.328    (8.96e-06): par = (9.186552 4.300271 0.2337328)
 --> irls.delta(previous, resid) = 5.27903e-05 -- *not* converged
robust iteration 23 
1463.125    (5.44e-05): par = (9.186552 4.300271 0.2337328)
1463.125    (5.43e-06): par = (9.186649 4.300199 0.2337374)
 --> irls.delta(previous, resid) = 3.45587e-05 -- *not* converged
robust iteration 24 
1462.976    (3.76e-05): par = (9.186649 4.300199 0.2337374)
1462.976    (3.69e-06): par = (9.186718 4.300149 0.2337406)
 --> irls.delta(previous, resid) = 2.36485e-05 -- *not* converged
robust iteration 25 
1462.869    (2.60e-05): par = (9.186718 4.300149 0.2337406)
1462.869    (2.53e-06): par = (9.186767 4.300114 0.2337428)
 --> irls.delta(previous, resid) = 1.62774e-05 -- *not* converged
robust iteration 26 
1462.794    (1.80e-05): par = (9.186767 4.300114 0.2337428)
1462.794    (1.75e-06): par = (9.186801 4.300089 0.2337443)
 --> irls.delta(previous, resid) = 1.12133e-05 -- *not* converged
robust iteration 27 
1462.741    (1.24e-05): par = (9.186801 4.300089 0.2337443)
1462.741    (1.22e-06): par = (9.186825 4.300073 0.2337453)
 --> irls.delta(previous, resid) = 7.72119e-06 -- *not* converged
robust iteration 28 
1462.706    (8.53e-06): par = (9.186825 4.300073 0.2337453)
> ## These failed in robustbase version 0.8-0 and earlier
> nlr2  <- update(nlr1, psi = psiTuk) # now *does* converge...
robust iteration 1 
21784.80    (1.66e+00): par = (4 1 1.2)
8950.648    (7.57e-01): par = (6.794198 2.077053 0.5341018)
7423.278    (6.19e-01): par = (9.060301 3.879916 0.2185499)
6817.584    (4.25e-01): par = (10.82425 1.938862 0.4933187)
6182.649    (2.57e-01): par = (9.035556 3.109244 0.3370087)
5913.322    (1.09e-01): par = (9.328708 2.761379 0.4451243)
5879.573    (5.99e-02): par = (9.040301 3.183598 0.3818532)
5868.447    (2.85e-02): par = (9.143668 2.956701 0.4148403)
5866.159    (1.51e-02): par = (9.072178 3.087634 0.3981463)
5865.492    (7.57e-03): par = (9.102801 3.024171 0.4068119)
5865.329    (3.91e-03): par = (9.085596 3.058034 0.4024024)
5865.285    (1.99e-03): par = (9.093983 3.041015 0.4046652)
5865.274    (1.02e-03): par = (9.089587 3.049808 0.4035098)
5865.271    (5.21e-04): par = (9.091807 3.045334 0.4041012)
5865.270    (2.66e-04): par = (9.090664 3.047628 0.4037989)
5865.270    (1.36e-04): par = (9.091246 3.046456 0.4039535)
5865.270    (6.97e-05): par = (9.090948 3.047056 0.4038745)
5865.270    (3.56e-05): par = (9.0911 3.046749 0.4039149)
5865.270    (1.82e-05): par = (9.091022 3.046906 0.4038942)
5865.270    (9.34e-06): par = (9.091062 3.046826 0.4039048)
 --> irls.delta(previous, resid) = 0.959769 -- *not* converged
robust iteration 2 
2467.708    (1.22e+00): par = (9.091062 3.046826 0.4039048)
1141.197    (2.08e-01): par = (9.406519 3.956961 0.2613981)
1096.394    (1.96e-02): par = (9.248399 3.874529 0.2786394)
1096.040    (3.16e-03): par = (9.212545 3.914507 0.2757742)
1096.030    (5.24e-04): par = (9.216718 3.908505 0.2762509)
1096.030    (8.71e-05): par = (9.215978 3.909552 0.2761716)
1096.030    (1.45e-05): par = (9.216099 3.909379 0.2761848)
1096.030    (2.41e-06): par = (9.216079 3.909408 0.2761826)
 --> irls.delta(previous, resid) = 0.6203 -- *not* converged
robust iteration 3 
581.9378    (2.93e-01): par = (9.216079 3.909408 0.2761826)
536.2659    (7.62e-03): par = (9.454548 3.942117 0.2660394)
536.2358    (2.91e-04): par = (9.455829 3.935567 0.2665224)
536.2357    (1.25e-05): par = (9.455582 3.935945 0.2665017)
536.2357    (5.44e-07): par = (9.455593 3.935929 0.2665025)
 --> irls.delta(previous, resid) = 0.0811759 -- *not* converged
robust iteration 4 
195.2050    (4.04e-01): par = (9.455593 3.935929 0.2665025)
167.8609    (6.05e-03): par = (9.723555 3.933725 0.2618007)
167.8547    (2.68e-05): par = (9.723259 3.933427 0.2619112)
167.8547    (2.49e-07): par = (9.723247 3.933446 0.2619102)
 --> irls.delta(previous, resid) = 0.0544385 -- *not* converged
robust iteration 5 
67.83645    (1.54e-01): par = (9.723247 3.933446 0.2619102)
66.26175    (1.69e-03): par = (9.810005 3.900449 0.2626903)
66.26156    (3.61e-08): par = (9.809999 3.900726 0.2626896)
 --> irls.delta(previous, resid) = 0.0127446 -- *not* converged
robust iteration 6 
68.65607    (1.48e-02): par = (9.809999 3.900726 0.2626896)
68.64105    (7.77e-06): par = (9.8154 3.901786 0.2625405)
 --> irls.delta(previous, resid) = 0.00130268 -- *not* converged
robust iteration 7 
68.56194    (1.24e-03): par = (9.8154 3.901786 0.2625405)
68.56183    (1.04e-07): par = (9.81588 3.901761 0.2625422)
 --> irls.delta(previous, resid) = 0.000115594 -- *not* converged
robust iteration 8 
68.53437    (2.65e-04): par = (9.81588 3.901761 0.2625422)
68.53436    (1.20e-07): par = (9.815926 3.901755 0.2625444)
 --> irls.delta(previous, resid) = 3.12703e-05 -- *not* converged
robust iteration 9 
68.52937    (7.47e-05): par = (9.815926 3.901755 0.2625444)
68.52937    (2.67e-08): par = (9.815928 3.901762 0.2625447)
 --> irls.delta(previous, resid) = 8.31962e-06 -- *not* converged
robust iteration 10 
68.52908    (2.31e-05): par = (9.815928 3.901762 0.2625447)
68.52908    (5.36e-09): par = (9.815926 3.901767 0.2625446)
 --> irls.delta(previous, resid) = 2.24775e-06 -- *not* converged
robust iteration 11 
68.52937    (7.98e-06): par = (9.815926 3.901767 0.2625446)
> ## check 'model' and dataClasses
> stopifnot(is.list(mod <- nlr2$model), is.data.frame(mod),
+           inherits(attr(mod, "terms"), "terms"),
+           identical(dCl <- attr(attr(mod, "terms"),"dataClasses"),
+                     nlr2$dataClasses),
+           identical(dCl, c(y = "numeric", x = "numeric")))
> ## 'port' ditto:
> nlr2. <- update(nlr2, algorithm= "port")
robust iteration 1 
  0:     10892.401:  4.00000  1.00000  1.20000
  1:     10001.455:  4.00121 0.945141  1.17950
  2:     5822.4271:  6.55887 0.616723  1.00486
  3:     4146.0465:  9.06774 0.873215 0.806372
  4:     3551.0730:  9.51133  1.46356 0.596710
  5:     3119.4331:  9.52710  2.15368 0.480492
  6:     2956.2769:  9.20892  2.88537 0.398621
  7:     2932.7614:  9.10178  3.02461 0.406998
  8:     2932.6685:  9.08526  3.05875 0.402308
  9:     2932.6436:  9.09417  3.04065 0.404713
 10:     2932.6350:  9.09108  3.04683 0.403900
 11:     2932.6350:  9.09105  3.04685 0.403902
 12:     2932.6350:  9.09105  3.04685 0.403901
 --> irls.delta(previous, resid) = 0.959769 -- *not* converged
robust iteration 2 
  0:     1233.8028:  9.09105  3.04685 0.403901
  1:     1072.1843:  9.12501  2.98906 0.396524
  2:     762.05575:  9.59748  2.93252 0.366301
  3:     567.22755:  9.50018  3.66706 0.279669
  4:     548.04143:  9.21121  3.90922 0.275495
  5:     547.97227:  9.21716  3.90791 0.276298
  6:     547.97191:  9.21591  3.90967 0.276162
  7:     547.97190:  9.21611  3.90938 0.276185
  8:     547.97190:  9.21608  3.90943 0.276181
  9:     547.97190:  9.21608  3.90942 0.276182
 --> irls.delta(previous, resid) = 0.620293 -- *not* converged
robust iteration 3 
  0:     290.95943:  9.21608  3.90942 0.276182
  1:     272.15767:  9.40607  3.87523 0.272617
  2:     268.11457:  9.45411  3.94013 0.266219
  3:     268.10958:  9.45575  3.93571 0.266515
  4:     268.10957:  9.45560  3.93594 0.266502
  5:     268.10957:  9.45560  3.93593 0.266502
 --> irls.delta(previous, resid) = 0.0811727 -- *not* converged
robust iteration 4 
  0:     97.597189:  9.45560  3.93593 0.266502
  1:     85.371453:  9.66151  3.91880 0.264581
  2:     83.922585:  9.72324  3.93384 0.261878
  3:     83.922509:  9.72326  3.93344 0.261910
  4:     83.922509:  9.72325  3.93345 0.261910
 --> irls.delta(previous, resid) = 0.0544377 -- *not* converged
robust iteration 5 
  0:     33.917669:  9.72325  3.93345 0.261910
  1:     33.160997:  9.79523  3.91585 0.262010
  2:     33.130367:  9.81000  3.90072 0.262688
  3:     33.130366:  9.81000  3.90072 0.262690
  4:     33.130366:  9.81000  3.90072 0.262690
 --> irls.delta(previous, resid) = 0.0127437 -- *not* converged
robust iteration 6 
  0:     34.327935:  9.81000  3.90072 0.262690
  1:     34.320424:  9.81540  3.90179 0.262541
  2:     34.320424:  9.81540  3.90179 0.262540
 --> irls.delta(previous, resid) = 0.00130297 -- *not* converged
robust iteration 7 
  0:     34.281184:  9.81540  3.90179 0.262540
  1:     34.281131:  9.81588  3.90176 0.262542
  2:     34.281131:  9.81588  3.90176 0.262542
 --> irls.delta(previous, resid) = 0.000115741 -- *not* converged
robust iteration 8 
  0:     34.267254:  9.81588  3.90176 0.262542
  1:     34.267252:  9.81593  3.90176 0.262544
  2:     34.267252:  9.81593  3.90176 0.262544
 --> irls.delta(previous, resid) = 3.13213e-05 -- *not* converged
robust iteration 9 
  0:     34.264705:  9.81593  3.90176 0.262544
  1:     34.264705:  9.81593  3.90176 0.262545
  2:     34.264705:  9.81593  3.90176 0.262545
 --> irls.delta(previous, resid) = 8.31314e-06 -- *not* converged
robust iteration 10 
  0:     34.264547:  9.81593  3.90176 0.262545
  1:     34.264547:  9.81593  3.90177 0.262545
  2:     34.264547:  9.81593  3.90177 0.262545
 --> irls.delta(previous, resid) = 2.24093e-06 -- *not* converged
robust iteration 11 
  0:     34.264687:  9.81593  3.90177 0.262545
  1:     34.264687:  9.81592  3.90177 0.262545
> nlr3  <- update(nlr1, psi = psiHamp)   # *does* converge, too...
robust iteration 1 
31454.69    (1.77e+00): par = (4 1 1.2)
8855.052    (7.14e-01): par = (9.566864 1.19518 0.570199)
7978.792    (5.46e-01): par = (9.343631 2.274515 0.3379566)
6393.905    (2.01e-01): par = (9.249048 2.846052 0.4479362)
6217.215    (7.50e-02): par = (9.014962 3.274209 0.3636331)
6198.861    (3.50e-02): par = (9.142487 2.962095 0.4021966)
6195.098    (1.82e-02): par = (9.050267 3.124659 0.3832724)
6194.058    (8.95e-03): par = (9.08679 3.049852 0.3929768)
6193.813    (4.55e-03): par = (9.066155 3.089743 0.388113)
6193.749    (2.28e-03): par = (9.075973 3.07008 0.39057)
6193.733    (1.15e-03): par = (9.070885 3.080104 0.3893352)
6193.729    (5.78e-04): par = (9.073408 3.075088 0.3899573)
6193.728    (2.91e-04): par = (9.072129 3.077621 0.3896442)
6193.728    (1.46e-04): par = (9.07277 3.076348 0.3898018)
6193.728    (7.37e-05): par = (9.072447 3.076989 0.3897225)
6193.728    (3.71e-05): par = (9.07261 3.076666 0.3897624)
6193.728    (1.87e-05): par = (9.072528 3.076829 0.3897424)
6193.728    (9.41e-06): par = (9.072569 3.076747 0.3897525)
 --> irls.delta(previous, resid) = 0.964508 -- *not* converged
robust iteration 2 
4155.741    (9.64e-01): par = (9.072569 3.076747 0.3897525)
2262.909    (8.11e-02): par = (9.270797 3.819417 0.2782037)
2248.527    (4.99e-03): par = (9.13059 3.789353 0.2842888)
2248.479    (7.32e-04): par = (9.120911 3.803003 0.2834302)
2248.478    (1.08e-04): par = (9.122084 3.801124 0.2835572)
2248.478    (1.60e-05): par = (9.121907 3.801407 0.2835384)
2248.478    (2.37e-06): par = (9.121933 3.801365 0.2835412)
 --> irls.delta(previous, resid) = 0.555917 -- *not* converged
robust iteration 3 
811.1612    (3.00e-01): par = (9.121933 3.801365 0.2835412)
745.7407    (1.68e-02): par = (9.340924 3.947205 0.2674901)
745.5399    (8.65e-04): par = (9.343033 3.931637 0.2686932)
745.5393    (5.20e-05): par = (9.342165 3.932965 0.2686211)
745.5393    (3.13e-06): par = (9.342214 3.932888 0.2686254)
 --> irls.delta(previous, resid) = 0.0938441 -- *not* converged
robust iteration 4 
459.6674    (2.13e-01): par = (9.342214 3.932888 0.2686254)
439.7304    (3.65e-03): par = (9.555448 3.934904 0.2644397)
439.7246    (9.41e-05): par = (9.556348 3.932772 0.2646233)
439.7246    (3.07e-06): par = (9.556279 3.93288 0.2646173)
 --> irls.delta(previous, resid) = 0.0445753 -- *not* converged
robust iteration 5 
178.9083    (2.64e-01): par = (9.556279 3.93288 0.2646173)
167.2243    (3.27e-03): par = (9.748598 3.905018 0.2630638)
167.2225    (5.77e-06): par = (9.748656 3.90538 0.2630903)
 --> irls.delta(previous, resid) = 0.033507 -- *not* converged
robust iteration 6 
81.93476    (1.22e-01): par = (9.748656 3.90538 0.2630903)
80.72725    (2.02e-04): par = (9.806133 3.901482 0.2629175)
80.72725    (1.49e-08): par = (9.806133 3.901503 0.2629184)
 --> irls.delta(previous, resid) = 0.011148 -- *not* converged
robust iteration 7 
90.48744    (1.24e-02): par = (9.806133 3.901503 0.2629184)
90.47359    (3.30e-05): par = (9.797875 3.907304 0.2627073)
90.47359    (1.74e-08): par = (9.797878 3.907303 0.2627077)
 --> irls.delta(previous, resid) = 0.00119868 -- *not* converged
robust iteration 8 
86.56107    (5.74e-03): par = (9.797878 3.907303 0.2627077)
86.55822    (1.20e-06): par = (9.800401 3.907005 0.262727)
 --> irls.delta(previous, resid) = 0.000609633 -- *not* converged
robust iteration 9 
88.08523    (1.80e-03): par = (9.800401 3.907005 0.262727)
88.08494    (1.06e-06): par = (9.799247 3.907513 0.2627094)
 --> irls.delta(previous, resid) = 0.000179469 -- *not* converged
robust iteration 10 
87.45760    (8.13e-04): par = (9.799247 3.907513 0.2627094)
87.45755    (2.97e-07): par = (9.799681 3.907392 0.2627146)
 --> irls.delta(previous, resid) = 8.61017e-05 -- *not* converged
robust iteration 11 
87.70611    (3.02e-04): par = (9.799681 3.907392 0.2627146)
87.70610    (1.30e-07): par = (9.7995 3.90746 0.2627121)
 --> irls.delta(previous, resid) = 3.08976e-05 -- *not* converged
robust iteration 12 
87.60540    (1.26e-04): par = (9.7995 3.90746 0.2627121)
87.60540    (5.04e-08): par = (9.799571 3.907437 0.262713)
 --> irls.delta(previous, resid) = 1.32335e-05 -- *not* converged
robust iteration 13 
87.64566    (4.95e-05): par = (9.799571 3.907437 0.262713)
87.64566    (3.70e-08): par = (9.799543 3.907447 0.2627126)
 --> irls.delta(previous, resid) = 5.11908e-06 -- *not* converged
robust iteration 14 
87.62944    (2.02e-05): par = (9.799543 3.907447 0.2627126)
87.62944    (1.45e-08): par = (9.799554 3.907443 0.2627128)
 --> irls.delta(previous, resid) = 2.10274e-06 -- *not* converged
robust iteration 15 
87.63595    (8.04e-06): par = (9.799554 3.907443 0.2627128)
> nlr3. <- update(nlr3, algorithm= "port")
robust iteration 1 
  0:     15727.347:  4.00000  1.00000  1.20000
  1:     14062.188:  3.91159 0.966688  1.18649
  2:     10672.136:  3.96238 0.834944  1.12760
  3:     7375.3147:  5.51478 0.709171 0.974142
  4:     4594.9111:  8.42560  1.49505 0.494567
  5:     3317.5213:  9.21757  2.96673 0.332383
  6:     3123.3083:  9.27814  2.82557 0.427745
  7:     3103.2632:  9.02262  3.20925 0.370497
  8:     3097.3210:  9.09129  3.05862 0.388622
  9:     3096.8691:  9.07490  3.07216 0.390326
 10:     3096.8652:  9.07138  3.07912 0.389458
 11:     3096.8641:  9.07315  3.07559 0.389895
 12:     3096.8639:  9.07226  3.07737 0.389675
 13:     3096.8638:  9.07271  3.07647 0.389786
 14:     3096.8638:  9.07248  3.07693 0.389730
 15:     3096.8638:  9.07259  3.07670 0.389758
 16:     3096.8638:  9.07254  3.07681 0.389744
 17:     3096.8638:  9.07256  3.07676 0.389751
 18:     3096.8638:  9.07255  3.07678 0.389748
 --> irls.delta(previous, resid) = 0.964509 -- *not* converged
robust iteration 2 
  0:     2077.8220:  9.07255  3.07678 0.389748
  1:     1742.6896:  8.96914  2.99037 0.382884
  2:     1409.1869:  9.27535  2.88218 0.364943
  3:     1168.2376:  9.40407  3.29733 0.313685
  4:     1126.3948:  9.19124  3.73501 0.284009
  5:     1124.2217:  9.12129  3.80190 0.283466
  6:     1124.2211:  9.12203  3.80121 0.283551
  7:     1124.2211:  9.12191  3.80140 0.283539
  8:     1124.2211:  9.12193  3.80137 0.283540
  9:     1124.2211:  9.12193  3.80138 0.283540
 --> irls.delta(previous, resid) = 0.555907 -- *not* converged
robust iteration 3 
  0:     405.57363:  9.12193  3.80138 0.283540
  1:     383.22138:  9.32457  3.78244 0.280212
  2:     373.43125:  9.38893  3.86693 0.271980
  3:     372.76699:  9.34042  3.93588 0.268415
  4:     372.76392:  9.34236  3.93267 0.268638
  5:     372.76391:  9.34221  3.93291 0.268624
  6:     372.76391:  9.34222  3.93289 0.268625
 --> irls.delta(previous, resid) = 0.0938412 -- *not* converged
robust iteration 4 
  0:     229.82801:  9.34222  3.93289 0.268625
  1:     220.49452:  9.52514  3.91639 0.266657
  2:     219.85718:  9.55571  3.93403 0.264547
  3:     219.85690:  9.55632  3.93283 0.264620
  4:     219.85690:  9.55629  3.93288 0.264617
  5:     219.85690:  9.55629  3.93288 0.264617
 --> irls.delta(previous, resid) = 0.0445741 -- *not* converged
robust iteration 5 
  0:     89.450051:  9.55629  3.93288 0.264617
  1:     85.536074:  9.64163  3.92824 0.264153
  2:     83.607433:  9.74860  3.90527 0.263079
  3:     83.607298:  9.74866  3.90538 0.263090
  4:     83.607298:  9.74866  3.90538 0.263090
 --> irls.delta(previous, resid) = 0.033507 -- *not* converged
robust iteration 6 
  0:     40.967123:  9.74866  3.90538 0.263090
  1:     40.363462:  9.80613  3.90148 0.262917
  2:     40.363460:  9.80613  3.90150 0.262918
  3:     40.363460:  9.80613  3.90150 0.262918
  4:     40.363460:  9.80613  3.90150 0.262918
 --> irls.delta(previous, resid) = 0.0111473 -- *not* converged
robust iteration 7 
  0:     45.243820:  9.80613  3.90150 0.262918
  1:     45.236898:  9.79787  3.90730 0.262707
  2:     45.236898:  9.79788  3.90730 0.262708
  3:     45.236898:  9.79788  3.90730 0.262708
 --> irls.delta(previous, resid) = 0.00119869 -- *not* converged
robust iteration 8 
  0:     43.280492:  9.79788  3.90730 0.262708
  1:     43.279068:  9.80040  3.90700 0.262727
  2:     43.279068:  9.80040  3.90701 0.262727
 --> irls.delta(previous, resid) = 0.000609605 -- *not* converged
robust iteration 9 
  0:     44.042626:  9.80040  3.90701 0.262727
  1:     44.042483:  9.79925  3.90751 0.262709
  2:     44.042483:  9.79925  3.90751 0.262709
 --> irls.delta(previous, resid) = 0.000179326 -- *not* converged
robust iteration 10 
  0:     43.728818:  9.79925  3.90751 0.262709
  1:     43.728789:  9.79968  3.90739 0.262715
  2:     43.728789:  9.79968  3.90739 0.262715
 --> irls.delta(previous, resid) = 8.59942e-05 -- *not* converged
robust iteration 11 
  0:     43.853039:  9.79968  3.90739 0.262715
  1:     43.853035:  9.79950  3.90746 0.262712
  2:     43.853035:  9.79950  3.90746 0.262712
 --> irls.delta(previous, resid) = 3.08655e-05 -- *not* converged
robust iteration 12 
  0:     43.802710:  9.79950  3.90746 0.262712
  1:     43.802709:  9.79957  3.90744 0.262713
  2:     43.802709:  9.79957  3.90744 0.262713
 --> irls.delta(previous, resid) = 1.32185e-05 -- *not* converged
robust iteration 13 
  0:     43.822827:  9.79957  3.90744 0.262713
  1:     43.822827:  9.79954  3.90745 0.262713
  2:     43.822827:  9.79954  3.90745 0.262713
 --> irls.delta(previous, resid) = 5.11564e-06 -- *not* converged
robust iteration 14 
  0:     43.814723:  9.79954  3.90745 0.262713
  1:     43.814723:  9.79955  3.90744 0.262713
  2:     43.814723:  9.79955  3.90744 0.262713
 --> irls.delta(previous, resid) = 2.09948e-06 -- *not* converged
robust iteration 15 
  0:     43.817973:  9.79955  3.90744 0.262713
  1:     43.817973:  9.79955  3.90744 0.262713
> summary(nlr2.)

Call:
nlrob(formula = y ~ a * (x + b * exp(-c * x)), data = d, start = list(a = 4, 
    b = 1, c = 1.2), psi = psiTuk, maxit = 50, algorithm = "port", 
    model = TRUE, trace = TRUE)

Residuals:
     Min       1Q   Median       3Q      Max 
-80.8710  -9.0677  -0.6409   0.8336   7.8824 

Parameters:
  Estimate Std. Error t value Pr(>|t|)    
a  9.81592    0.30133   32.58 1.19e-10 ***
b  3.90177    0.25445   15.33 9.32e-08 ***
c  0.26254    0.01298   20.22 8.23e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Robust residual standard error: 2.871 
Convergence in 11 IRWLS iterations

Robustness weights: 
 4 observations c(1,10,11,12) are outliers with |weight| = 0 ( < 0.0062); 
 3 weights are ~= 1. The remaining 9 ones are
     2      3      5      6      9     13     14     15     16 
0.9665 0.6199 0.4310 0.9894 0.9944 0.9636 0.9843 0.9465 0.9540 
> summary(nlr3.)

Call:
nlrob(formula = y ~ a * (x + b * exp(-c * x)), data = d, start = list(a = 4, 
    b = 1, c = 1.2), psi = psiHamp, maxit = 50, algorithm = "port", 
    model = TRUE, trace = TRUE)

Residuals:
     Min       1Q   Median       3Q      Max 
-80.8093  -9.1350  -0.6438   0.8983   7.8419 

Parameters:
  Estimate Std. Error t value Pr(>|t|)    
a  9.79955    0.27069   36.20 6.15e-12 ***
b  3.90744    0.23112   16.91 1.10e-08 ***
c  0.26271    0.01177   22.32 7.34e-10 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Robust residual standard error: 2.81 
Convergence in 15 IRWLS iterations

Robustness weights: 
 3 observations c(1,10,12) are outliers with |weight| = 0 ( < 0.0062); 
 10 weights are ~= 1. The remaining 3 ones are
      3       5      11 
0.60160 0.48469 0.05089 
> i. <- -c(2, 15) # <- drop 'call' and 'iter' components
> stopifnot(all.equal(nlr2[i.], nlr2.[i.], tolerance = 2e-5, check.environment = FALSE),
+           all.equal(nlr3[i.], nlr3.[i.], tolerance = 1e-4, check.environment = FALSE),
+           ## The redescending psi() give some exact 0 weights :
+ 	  identical(which(abs(nlr2$rweights) < 1e-9), c(1L, 10 :12)),
+ 	  identical(which(abs(nlr3$rweights) < 1e-9), c(1L, 10L,12L))
+ 	  )
> 
> ## Different example with more data:
> pp <- list(a=10, b=4, c=1/4)
> x <- seq(-6,9, by = 1/8)
> f.x <- with(pp, a*(x + b*exp(-c*x)))
> set.seed(6); y <- y0 <- f.x + 4*rnorm(x)
> iO <- c(2:3,20,70:71,90); y[iO] <- y[iO] + 32*c(-1,-1,1)*(2+rlnorm(iO)); y <- round(y)
> plot(x,y); lines(x, f.x, col="tomato", lty = 2)
> dd <- data.frame(x,y)
> 
> nlc1 <- nls(formula(nlr1), start = coef(nlr1), data=dd, trace=TRUE)
46029.40    (1.20e-01): par = (9.186825 4.300073 0.2337453)
45400.15    (1.04e-02): par = (9.387432 4.478143 0.2207645)
45395.72    (1.12e-03): par = (9.407647 4.442873 0.2225454)
45395.67    (1.29e-04): par = (9.403353 4.448036 0.2223394)
45395.67    (1.49e-05): par = (9.403824 4.447463 0.2223632)
45395.67    (1.73e-06): par = (9.403769 4.447529 0.2223605)
> nlR1 <- update(nlr1, data = dd)# update the model with the new data
robust iteration 1 
       3168834. (6.39e+00): par = (4 1 1.2)
2561749.    (6.78e+00): par = (11.08659 -0.6571938 1.007253)
174677.5    (1.27e+00): par = (11.20292 0.1094524 1.120573)
157751.5    (2.34e+00): par = (11.19533 0.5517858 0.2485101)
150491.1    (2.30e+00): par = (10.21642 3.396859 0.4987888)
30722.38    (5.16e-01): par = (10.74164 3.30795 0.3607351)
24480.55    (3.56e-02): par = (10.23807 3.687561 0.2877978)
24450.03    (9.67e-04): par = (10.13453 3.718308 0.2839636)
24450.01    (6.77e-05): par = (10.13686 3.715617 0.2841939)
24450.01    (4.75e-06): par = (10.13669 3.715809 0.2841778)
 --> irls.delta(previous, resid) = 0.985635 -- *not* converged
robust iteration 2 
7144.093    (6.60e-01): par = (10.13669 3.715809 0.2841778)
4997.811    (2.18e-02): par = (9.929966 3.999455 0.2515935)
4995.443    (2.25e-04): par = (9.89099 4.01926 0.2507756)
4995.443    (3.18e-06): par = (9.891172 4.019093 0.2507889)
 --> irls.delta(previous, resid) = 0.299322 -- *not* converged
robust iteration 3 
4429.342    (5.10e-02): par = (9.891172 4.019093 0.2507889)
4417.861    (1.47e-04): par = (9.911611 3.992386 0.2508396)
4417.861    (1.30e-08): par = (9.911606 3.992449 0.2508395)
 --> irls.delta(previous, resid) = 0.0168192 -- *not* converged
robust iteration 4 
4351.250    (8.70e-03): par = (9.911606 3.992449 0.2508395)
4350.921    (1.98e-06): par = (9.913543 3.988428 0.2508398)
 --> irls.delta(previous, resid) = 0.00288391 -- *not* converged
robust iteration 5 
4300.932    (2.12e-03): par = (9.913543 3.988428 0.2508398)
4300.912    (4.31e-06): par = (9.914509 3.986762 0.250877)
 --> irls.delta(previous, resid) = 0.000677833 -- *not* converged
robust iteration 6 
4282.129    (6.56e-04): par = (9.914509 3.986762 0.250877)
4282.127    (2.32e-06): par = (9.914907 3.98611 0.2508969)
 --> irls.delta(previous, resid) = 0.000205702 -- *not* converged
robust iteration 7 
4287.079    (2.47e-05): par = (9.914907 3.98611 0.2508969)
4287.079    (7.40e-08): par = (9.914874 3.986124 0.2508963)
 --> irls.delta(previous, resid) = 8.0224e-06 -- *not* converged
robust iteration 8 
4287.096    (2.91e-06): par = (9.914874 3.986124 0.2508963)
> summary(nlR1)

Call:
nlrob(formula = y ~ a * (x + b * exp(-c * x)), data = dd, start = list(a = 4, 
    b = 1, c = 1.2), maxit = 50, algorithm = "default", model = TRUE, 
    trace = TRUE)

Residuals:
      Min        1Q    Median        3Q       Max 
-104.3318   -2.8778   -0.2577    2.6657   94.8054 

Parameters:
  Estimate Std. Error t value Pr(>|t|)    
a 9.914874   0.127151   77.98   <2e-16 ***
b 3.986124   0.100492   39.67   <2e-16 ***
c 0.250896   0.004481   55.99   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Robust residual standard error: 4.021 
Convergence in 8 IRWLS iterations

Robustness weights: 
 94 weights are ~= 1. The remaining 27 ones are summarized as
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.05183 0.52880 0.70780 0.62570 0.88150 0.97880 
> lines(x, predict(nlc1), col=3)
> lines(x, predict(nlR1), col=4)
> legend("top", c("f(x)", "least squares", "robust"),
+        col=c("tomato", palette()[3:4]), lty=c(2,1,1))
> 
> ## These both now *do* converge, but failed earlier
> (nlbi <- update(nlR1, psi = psiTuk))
robust iteration 1 
218821.4    (2.03e+00): par = (4 1 1.2)
67190.96    (1.41e+00): par = (11.47967 1.005964 0.5032814)
54469.20    (1.19e+00): par = (10.80906 3.073192 0.1285173)
41356.44    (9.35e-01): par = (12.82997 2.93352 0.431285)
22089.84    (8.17e-02): par = (10.64003 3.251034 0.3543112)
21937.77    (4.50e-03): par = (10.50597 3.386588 0.3320926)
21937.31    (1.79e-04): par = (10.4895 3.399995 0.3309259)
21937.31    (8.43e-06): par = (10.48906 3.400513 0.3308711)
 --> irls.delta(previous, resid) = 0.973072 -- *not* converged
robust iteration 2 
2708.684    (1.03e+00): par = (10.48906 3.400513 0.3308711)
1316.352    (1.26e-01): par = (10.125 3.865055 0.2631006)
1295.806    (1.77e-03): par = (10.01052 3.922658 0.2617063)
1295.802    (8.23e-07): par = (10.01035 3.923444 0.2616981)
 --> irls.delta(previous, resid) = 0.547283 -- *not* converged
robust iteration 3 
1727.818    (4.46e-01): par = (10.01035 3.923444 0.2616981)
1441.477    (6.97e-03): par = (9.952053 3.961289 0.2543473)
1441.407    (3.22e-06): par = (9.949315 3.962943 0.2542019)
 --> irls.delta(previous, resid) = 0.0932736 -- *not* converged
robust iteration 4 
1370.754    (7.09e-02): par = (9.949315 3.962943 0.2542019)
1363.893    (1.47e-04): par = (9.946841 3.956505 0.2536626)
1363.893    (1.03e-07): par = (9.946816 3.956524 0.25366)
 --> irls.delta(previous, resid) = 0.0137294 -- *not* converged
robust iteration 5 
1356.836    (1.32e-02): par = (9.946816 3.956524 0.25366)
1356.601    (3.26e-06): par = (9.947287 3.954145 0.2536149)
 --> irls.delta(previous, resid) = 0.00251554 -- *not* converged
robust iteration 6 
1360.308    (2.00e-03): par = (9.947287 3.954145 0.2536149)
1360.303    (6.55e-07): par = (9.947455 3.953883 0.2536008)
 --> irls.delta(previous, resid) = 0.000386631 -- *not* converged
robust iteration 7 
1365.090    (5.26e-04): par = (9.947455 3.953883 0.2536008)
1365.089    (6.03e-07): par = (9.947463 3.954141 0.2535868)
 --> irls.delta(previous, resid) = 9.55039e-05 -- *not* converged
robust iteration 8 
1365.378    (1.16e-04): par = (9.947463 3.954141 0.2535868)
1365.378    (1.26e-07): par = (9.947459 3.954201 0.253584)
 --> irls.delta(previous, resid) = 2.08128e-05 -- *not* converged
robust iteration 9 
1365.381    (1.84e-05): par = (9.947459 3.954201 0.253584)
1365.381    (1.84e-08): par = (9.947458 3.954211 0.2535835)
 --> irls.delta(previous, resid) = 3.30327e-06 -- *not* converged
robust iteration 10 
1365.378    (2.51e-06): par = (9.947458 3.954211 0.2535835)
Robustly fitted nonlinear regression model
  model:  y ~ a * (x + b * exp(-c * x)) 
   data:  dd 
        a         b         c 
9.9474582 3.9542106 0.2535835 
 status:  converged 
> (nlFH <- update(nlR1, psi = psiHamp))
robust iteration 1 
      270384. (2.24e+00): par = (4 1 1.2)
72286.00    (1.42e+00): par = (11.46105 0.8970769 0.5403462)
53715.74    (1.15e+00): par = (11.16759 1.972172 0.2935121)
23380.24    (8.02e-02): par = (10.44915 3.349901 0.3414424)
23228.39    (2.56e-03): par = (10.44693 3.435853 0.3229528)
23228.24    (4.66e-05): par = (10.43676 3.442012 0.3224136)
23228.24    (1.20e-06): par = (10.43664 3.442148 0.3223996)
 --> irls.delta(previous, resid) = 0.975764 -- *not* converged
robust iteration 2 
3706.949    (1.28e+00): par = (10.43664 3.442148 0.3223996)
1417.131    (1.13e-01): par = (10.08804 3.889039 0.2600798)
1399.404    (2.08e-03): par = (9.971514 3.952694 0.2574098)
1399.398    (1.32e-07): par = (9.971213 3.953574 0.257405)
 --> irls.delta(previous, resid) = 0.528145 -- *not* converged
robust iteration 3 
1659.375    (2.56e-01): par = (9.971213 3.953574 0.257405)
1557.143    (2.38e-03): par = (9.950309 3.958075 0.2539913)
1557.134    (1.28e-06): par = (9.949668 3.95845 0.2539479)
 --> irls.delta(previous, resid) = 0.0520968 -- *not* converged
robust iteration 4 
1468.602    (5.11e-02): par = (9.949668 3.95845 0.2539479)
1464.781    (1.81e-05): par = (9.955355 3.946951 0.2538397)
1464.781    (3.19e-08): par = (9.955351 3.946963 0.2538392)
 --> irls.delta(previous, resid) = 0.00985236 -- *not* converged
robust iteration 5 
1489.146    (8.82e-03): par = (9.955351 3.946963 0.2538392)
1489.030    (9.97e-06): par = (9.953683 3.948046 0.253687)
 --> irls.delta(previous, resid) = 0.00178012 -- *not* converged
robust iteration 6 
1491.851    (1.75e-03): par = (9.953683 3.948046 0.253687)
1491.846    (2.49e-06): par = (9.953151 3.94864 0.2536412)
 --> irls.delta(previous, resid) = 0.000357032 -- *not* converged
robust iteration 7 
1493.922    (4.23e-04): par = (9.953151 3.94864 0.2536412)
1493.922    (7.86e-07): par = (9.952956 3.948936 0.2536263)
 --> irls.delta(previous, resid) = 8.12119e-05 -- *not* converged
robust iteration 8 
1494.386    (1.16e-04): par = (9.952956 3.948936 0.2536263)
1494.386    (1.92e-07): par = (9.952908 3.949019 0.2536227)
 --> irls.delta(previous, resid) = 2.15116e-05 -- *not* converged
robust iteration 9 
1494.524    (3.50e-05): par = (9.952908 3.949019 0.2536227)
1494.524    (4.54e-08): par = (9.952897 3.949041 0.2536219)
 --> irls.delta(previous, resid) = 6.40108e-06 -- *not* converged
robust iteration 10 
1494.563    (1.06e-05): par = (9.952897 3.949041 0.2536219)
1494.563    (7.79e-09): par = (9.952894 3.949047 0.2536217)
 --> irls.delta(previous, resid) = 1.95479e-06 -- *not* converged
robust iteration 11 
1494.573    (3.15e-06): par = (9.952894 3.949047 0.2536217)
Robustly fitted nonlinear regression model
  model:  y ~ a * (x + b * exp(-c * x)) 
   data:  dd 
        a         b         c 
9.9528938 3.9490474 0.2536217 
 status:  converged 
> lines(x, predict(nlbi), col=5)
> lines(x, predict(nlFH), col=6)
> 
> stopifnot(nlR1$status == "converged", nlbi$status == "converged",
+ 	  nlFH$status == "converged")
> assert.EQ(coef(nlR1), c(a=9.914874,    b=3.98612416,  c=0.250896252),  tol = 4e-9)
> assert.EQ(coef(nlbi), c(a=9.947458207, b=3.954210623, c=0.2535835248), tol = 4e-9)
> ## This is suddently quite different :  ???!?!??
> ## assert.EQ(coef(nlFH), c(a=9.94242831, b=3.97370746, c=0.252907618))
> assert.EQ(coef(nlFH),    c(a=9.952893755,b=3.949047387,c=0.2536216541), tol = 1e-7)
> assert.EQ(1000*diag(vcov(nlR1)),
+           c(a=16.167493, b=10.0986644, c=0.0200814189), tol = 7e-7, giveRE=TRUE)
Mean relative difference: 1.302957e-08
> assert.EQ(1000*local({V <- vcov(nlFH); V[lower.tri(V, diag=TRUE)]}),
+           c(16.33774615, -9.704702857, 0.3149189329,
+             10.03560556, -0.4079936961, 0.02039106329), tol = 7e-7)
> assert.EQ(predict(nlR1), predict(nlbi), tol = 0.05, giveRE=TRUE)
Mean relative difference: 0.004298822
> assert.EQ(predict(nlR1), predict(nlFH), tol = 0.05, giveRE=TRUE)
Mean relative difference: 0.004179098
> 
> nlFH2 <- update(nlFH, psi = .Mwgt.psi1("Hampel", c(2,4,8)))
robust iteration 1 
350706.2    (2.49e+00): par = (4 1 1.2)
85829.27    (1.45e+00): par = (11.48608 0.7331785 0.5917242)
73419.94    (1.34e+00): par = (11.26332 1.811758 0.2748707)
27827.79    (2.48e-01): par = (10.5316 3.318498 0.3672919)
26205.58    (1.46e-02): par = (10.52134 3.401801 0.3279451)
26199.95    (3.27e-04): par = (10.48292 3.422433 0.3249664)
26199.95    (9.74e-06): par = (10.48202 3.423437 0.3248697)
 --> irls.delta(previous, resid) = 0.974981 -- *not* converged
robust iteration 2 
5431.585    (1.58e+00): par = (10.48202 3.423437 0.3248697)
1567.259    (1.27e-01): par = (10.10363 3.889287 0.2591098)
1542.356    (3.19e-03): par = (9.96365 3.969473 0.255059)
1542.341    (1.05e-06): par = (9.962861 3.971006 0.2550389)
 --> irls.delta(previous, resid) = 0.560849 -- *not* converged
robust iteration 3 
1767.891    (1.59e-01): par = (9.962861 3.971006 0.2550389)
1724.468    (9.74e-04): par = (9.941902 3.97751 0.2527665)
1724.467    (5.63e-07): par = (9.9416 3.977706 0.2527468)
 --> irls.delta(previous, resid) = 0.0333368 -- *not* converged
robust iteration 4 
1696.769    (7.61e-03): par = (9.9416 3.977706 0.2527468)
1696.671    (1.13e-05): par = (9.942364 3.973438 0.2529201)
1696.671    (1.03e-08): par = (9.942365 3.973435 0.2529204)
 --> irls.delta(previous, resid) = 0.00145877 -- *not* converged
robust iteration 5 
1699.315    (6.55e-04): par = (9.942365 3.973435 0.2529204)
1699.315    (4.38e-07): par = (9.942432 3.973736 0.2529063)
 --> irls.delta(previous, resid) = 0.000125732 -- *not* converged
robust iteration 6 
1699.078    (5.94e-05): par = (9.942432 3.973736 0.2529063)
1699.078    (3.91e-08): par = (9.942428 3.973707 0.2529076)
 --> irls.delta(previous, resid) = 1.13892e-05 -- *not* converged
robust iteration 7 
1699.099    (5.29e-06): par = (9.942428 3.973707 0.2529076)
> ## TODO: and compare
> ## TODO: same with Tukey
> 
> 
> ##----- *Vector* parameters indexed by factor  levels -------------
> ##----- MM: ~/R/MM/Pkg-ex/robustbase/nlrob-vectorpar.R
> 
> data(biomassTill)## see also smaller example in ../man/biomassTill.Rd
> 
> if(!dev.interactive(orNone=TRUE))  pdf("nlrob-biomT.pdf")
> 
> require(lattice)
Loading required package: lattice
> xyplot(Biomass ~ DVS | Tillage, data = biomassTill)
> xyplot(Biom.2  ~ DVS | Tillage, data = biomassTill)
> 
> ## starting values
> m0.st <- list(Wm = rep(200, 3),
+                a = rep(  1, 3),
+                b = rep(  2, 3))
> ##-> nls(), even with -expm1(.) fails to start properly (and hence nlrob() fails too):
> try(
+ m.c0 <- nls(Biomass ~ Wm[Tillage] * (- expm1(-(DVS/a[Tillage])^b[Tillage])),
+             data = biomassTill, start = m0.st, trace=TRUE)
+ )
587654.1    (9.81e-01): par = (200 200 200 1 1 1 2 2 2)
482258.8    (7.99e-01): par = (272.4978 374.0926 409.5831 1.799294 2.134555 2.012146 1.402013 1.257745 2.20363)
Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) : 
  Missing value or an infinity produced when evaluating the model
> 
> ## several other versions of the above fail similarly.  This works:
> m00st <- list(Wm = rep(300,  3),
+                a = rep( 1.5, 3),
+                b = rep( 2.2, 3))
> m.c00 <- nls(Biomass ~ Wm[Tillage] * (- expm1(-(DVS/a[Tillage])^b[Tillage])),
+             data = biomassTill, start = m00st, trace=TRUE)
420613.6    (6.51e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
      344484. (4.11e-01): par = (362.5376 497.0366 343.0101 2.020939 2.224128 1.132643 2.220821 2.385964 3.655383)
299205.0    (1.24e-01): par = (457.7625 577.6557 372.3018 2.311593 2.066905 1.363035 2.39158 2.687003 2.986474)
294696.7    (1.33e-02): par = (487.9168 622.4386 380.0351 2.338248 2.203776 1.37486 2.399665 2.571926 3.506427)
294644.3    (8.78e-04): par = (490.3131 609.5898 380.0224 2.343957 2.176673 1.371195 2.396815 2.601775 3.591947)
294644.1    (1.89e-04): par = (489.8298 616.8028 380.0659 2.342473 2.192439 1.371285 2.397443 2.59302 3.594869)
294644.1    (4.95e-05): par = (489.9346 615.161 380.064 2.342793 2.188804 1.371278 2.39731 2.595325 3.594965)
294644.1    (1.34e-05): par = (489.9127 615.6588 380.064 2.342726 2.189888 1.371278 2.397338 2.594692 3.594968)
294644.1    (3.61e-06): par = (489.9173 615.528 380.064 2.34274 2.189602 1.371278 2.397332 2.594862 3.594968)
> 
> ## These were the "true" beta for simulating in creation of {Biomass, Biom.2}:
> m1.st <- list(Wm = c(219.8, 265.9, 343.4),
+                a = c(1.461, 1.493, 1.294),
+                b = c(2.889, 2.838, 4.046))
> 
> m.cl <- nls(Biomass ~ Wm[Tillage] * (1 - exp(-(DVS/a[Tillage])^b[Tillage])),
+             data = biomassTill, start = m00st, trace=TRUE)
420613.6    (6.51e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
      344484. (4.11e-01): par = (362.5376 497.0366 343.0101 2.020939 2.224128 1.132643 2.220821 2.385964 3.655383)
299205.0    (1.24e-01): par = (457.7625 577.6557 372.3018 2.311593 2.066905 1.363035 2.39158 2.687003 2.986474)
294696.7    (1.33e-02): par = (487.9168 622.4387 380.0351 2.338248 2.203776 1.37486 2.399665 2.571926 3.506427)
294644.3    (8.78e-04): par = (490.3131 609.5898 380.0224 2.343957 2.176673 1.371195 2.396815 2.601775 3.591947)
294644.1    (1.89e-04): par = (489.8298 616.8028 380.0659 2.342473 2.192438 1.371285 2.397443 2.59302 3.594869)
294644.1    (4.95e-05): par = (489.9345 615.1608 380.064 2.342793 2.188804 1.371278 2.39731 2.595326 3.594965)
294644.1    (1.34e-05): par = (489.9126 615.6589 380.064 2.342726 2.189888 1.371278 2.397338 2.594691 3.594968)
294644.1    (3.61e-06): par = (489.9173 615.5279 380.064 2.34274 2.189602 1.371278 2.397332 2.594862 3.594968)
> ## this now fails to converge:
> try( # "singular gradient"
+ m.c2 <- nls(Biom.2 ~ Wm[Tillage] * (1 - exp(-(DVS/a[Tillage])^b[Tillage])),
+             data = biomassTill, start = m00st, trace=TRUE)
+ )
438775.3    (7.04e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
Error in nls(Biom.2 ~ Wm[Tillage] * (1 - exp(-(DVS/a[Tillage])^b[Tillage])),  : 
  singular gradient
> 
> str(C1 <- nls.control(minFactor=1e-6, warnOnly=TRUE, printEval=TRUE, maxiter=500))
List of 7
 $ maxiter    : num 500
 $ tol        : num 1e-05
 $ minFactor  : num 1e-06
 $ printEval  : logi TRUE
 $ warnOnly   : logi TRUE
 $ scaleOffset: num 0
 $ nDcentral  : logi FALSE
> 
> try(
+ m.c2 <- nls(Biom.2 ~ Wm[Tillage] * (1 - exp(-(DVS/a[Tillage])^b[Tillage])),
+                 data = biomassTill, start = m00st, trace=TRUE, control=C1)
+ )
438775.3    (7.04e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
  It.   1, fac=           1, eval (no.,total): ( 1,  1):Warning message:
In nls(Biom.2 ~ Wm[Tillage] * (1 - exp(-(DVS/a[Tillage])^b[Tillage])),  :
  singular gradient
> ## fails (!) too {numericDeriv() in iteration 129} even though we have
> ## 'warnOnly' ! ==> bug in nls()  !!!!!!!!!!!!!!!!!!!!!!!!!!!
> 
> ## -expm1(u) is better than (1 - exp(u)) :
> m.c00 <- nls(Biom.2 ~ Wm[Tillage] * (- expm1(-(DVS/a[Tillage])^b[Tillage])),
+              data = biomassTill, start = m00st, trace=TRUE, control=C1)
438775.3    (7.04e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
  It.   1, fac=           1, eval (no.,total): ( 1,  1):Warning message:
In nls(Biom.2 ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage])),  :
  singular gradient
> ## "fails" but returns .. very bad..
> m.c00
Nonlinear regression model
  model: Biom.2 ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage]))
   data: biomassTill
     Wm1      Wm2      Wm3       a1       a2       a3       b1       b2 
579.5709 -65.2797 343.0101   3.0370   0.1953   1.1326   0.1499   3.6698 
      b3 
  3.6554 
 residual sum-of-squares: 1755085

Number of iterations till stop: 0 
Achieved convergence tolerance: 0.7041
Reason stopped: singular gradient
> ## Use better starting values, as we have such problems:
> m.c2 <- nls(Biom.2 ~ Wm[Tillage] * (- expm1(-(DVS/a[Tillage])^b[Tillage])),
+             data = biomassTill, start = m1.st, trace=TRUE, control=C1)
346662.5    (3.97e-01): par = (219.8 265.9 343.4 1.461 1.493 1.294 2.889 2.838 4.046)
  It.   1, fac=           1, eval (no.,total): ( 1,  1): new dev = 851368
  It.   1, fac=         0.5, eval (no.,total): ( 2,  2): new dev = 312626
312625.9    (3.04e-01): par = (309.4095 153.7503 359.7017 1.892067 1.100219 1.328286 1.430481 3.275306 3.800108)
  It.   2, fac=           1, eval (no.,total): ( 1,  3): new dev = 4.28282e+07
  It.   2, fac=         0.5, eval (no.,total): ( 2,  4): new dev = 2.57229e+06
  It.   2, fac=        0.25, eval (no.,total): ( 3,  5): new dev = 384268
  It.   2, fac=       0.125, eval (no.,total): ( 4,  6): new dev = 315274
  It.   2, fac=      0.0625, eval (no.,total): ( 5,  7): new dev = 311399
311399.5    (3.01e-01): par = (390.7912 153.1392 360.8844 2.477 1.091192 1.330795 1.2808 3.372159 3.786863)
  It.   3, fac=       0.125, eval (no.,total): ( 1,  8): new dev = 334082
  It.   3, fac=      0.0625, eval (no.,total): ( 2,  9): new dev = 312701
  It.   3, fac=     0.03125, eval (no.,total): ( 3, 10): new dev = 310867
310866.6    (3.00e-01): par = (479.6162 152.8703 361.4434 3.149754 1.08712 1.33198 1.20463 3.420235 3.780688)
  It.   4, fac=      0.0625, eval (no.,total): ( 1, 11): new dev = 316839
  It.   4, fac=     0.03125, eval (no.,total): ( 2, 12): new dev = 311168
  It.   4, fac=    0.015625, eval (no.,total): ( 3, 13): new dev = 310551
310550.8    (2.99e-01): par = (560.1891 152.7435 361.7153 3.780869 1.085179 1.332556 1.165901 3.444206 3.777705)
  It.   5, fac=     0.03125, eval (no.,total): ( 1, 14): new dev = 311781
  It.   5, fac=    0.015625, eval (no.,total): ( 2, 15): new dev = 310448
310447.6    (2.99e-01): par = (682.7773 152.6203 361.9834 4.759825 1.083281 1.333124 1.126675 3.468146 3.774771)
  It.   6, fac=     0.03125, eval (no.,total): ( 1, 16): new dev = 313578
  It.   6, fac=    0.015625, eval (no.,total): ( 2, 17): new dev = 310756
  It.   6, fac=   0.0078125, eval (no.,total): ( 3, 18): new dev = 310336
310335.7    (2.99e-01): par = (784.0033 152.5603 362.1155 5.586798 1.082353 1.333405 1.106825 3.480102 3.773329)
  It.   7, fac=    0.015625, eval (no.,total): ( 1, 19): new dev = 311007
  It.   7, fac=   0.0078125, eval (no.,total): ( 2, 20): new dev = 310316
310315.7    (2.99e-01): par = (925.9601 152.5012 362.2468 6.761122 1.081436 1.333683 1.086805 3.492051 3.771899)
  It.   8, fac=    0.015625, eval (no.,total): ( 1, 21): new dev = 311576
  It.   8, fac=   0.0078125, eval (no.,total): ( 2, 22): new dev = 310442
  It.   8, fac=  0.00390625, eval (no.,total): ( 3, 23): new dev = 310254
310254.4    (2.99e-01): par = (1031.081 152.472 362.312 7.642702 1.080982 1.333821 1.076715 3.498023 3.77119)
  It.   9, fac=   0.0078125, eval (no.,total): ( 1, 24): new dev = 310489
  It.   9, fac=  0.00390625, eval (no.,total): ( 2, 25): new dev = 310222
310221.9    (2.99e-01): par = (1165.986 152.443 362.377 8.782302 1.080531 1.333959 1.066571 3.503993 3.770484)
  It.  10, fac=   0.0078125, eval (no.,total): ( 1, 26): new dev = 310603
  It.  10, fac=  0.00390625, eval (no.,total): ( 2, 27): new dev = 310229
  It.  10, fac=  0.00195312, eval (no.,total): ( 3, 28): new dev = 310176
310176.3    (2.99e-01): par = (1255.211 152.4287 362.4094 9.541774 1.080307 1.334027 1.061472 3.506977 3.770133)
  It.  11, fac=  0.00390625, eval (no.,total): ( 1, 29): new dev = 310208
  It.  11, fac=  0.00195312, eval (no.,total): ( 2, 30): new dev = 310137
310137.5    (2.99e-01): par = (1360.59 152.4143 362.4417 10.44226 1.080083 1.334096 1.056356 3.509961 3.769782)
  It.  12, fac=  0.00390625, eval (no.,total): ( 1, 31): new dev = 310200
  It.  12, fac=  0.00195312, eval (no.,total): ( 2, 32): new dev = 310107
310107.0    (2.98e-01): par = (1486.756 152.4 362.4739 11.52468 1.07986 1.334164 1.051224 3.512944 3.769432)
  It.  13, fac=  0.00390625, eval (no.,total): ( 1, 33): new dev = 310207
  It.  13, fac=  0.00195312, eval (no.,total): ( 2, 34): new dev = 310087
310086.8    (2.98e-01): par = (1640.24 152.3858 362.5061 12.84688 1.079637 1.334232 1.046076 3.515927 3.769082)
  It.  14, fac=  0.00390625, eval (no.,total): ( 1, 35): new dev = 310234
  It.  14, fac=  0.00195312, eval (no.,total): ( 2, 36): new dev = 310079
310079.4    (2.98e-01): par = (1830.52 152.3716 362.5383 14.49288 1.079415 1.3343 1.040912 3.51891 3.768734)
  It.  15, fac=  0.00390625, eval (no.,total): ( 1, 37): new dev = 310286
  It.  15, fac=  0.00195312, eval (no.,total): ( 2, 38): new dev = 310088
  It.  15, fac= 0.000976562, eval (no.,total): ( 3, 39): new dev = 310058
310058.0    (2.98e-01): par = (1951.173 152.3645 362.5543 15.54103 1.079305 1.334334 1.038322 3.520401 3.76856)
  It.  16, fac=  0.00195312, eval (no.,total): ( 1, 40): new dev = 310077
  It.  16, fac= 0.000976562, eval (no.,total): ( 2, 41): new dev = 310039
310039.5    (2.98e-01): par = (2089.638 152.3575 362.5703 16.74653 1.079194 1.334368 1.035728 3.521892 3.768386)
  It.  17, fac=  0.00195312, eval (no.,total): ( 1, 42): new dev = 310070
  It.  17, fac= 0.000976562, eval (no.,total): ( 2, 43): new dev = 310024
310024.1    (2.98e-01): par = (2250.045 152.3504 362.5864 18.14612 1.079084 1.334402 1.033129 3.523383 3.768212)
  It.  18, fac=  0.00195312, eval (no.,total): ( 1, 44): new dev = 310069
  It.  18, fac= 0.000976562, eval (no.,total): ( 2, 45): new dev = 310012
310012.4    (2.98e-01): par = (2437.875 152.3434 362.6024 19.78859 1.078974 1.334436 1.030525 3.524874 3.768039)
  It.  19, fac=  0.00195312, eval (no.,total): ( 1, 46): new dev = 310073
  It.  19, fac= 0.000976562, eval (no.,total): ( 2, 47): new dev = 310005
310005.2    (2.98e-01): par = (2660.542 152.3364 362.6184 21.74002 1.078864 1.33447 1.027917 3.526365 3.767866)
  It.  20, fac=  0.00195312, eval (no.,total): ( 1, 48): new dev = 310085
  It.  20, fac= 0.000976562, eval (no.,total): ( 2, 49): new dev = 310003
310003.4    (2.98e-01): par = (2928.314 152.3294 362.6343 24.09199 1.078754 1.334504 1.025304 3.527856 3.767693)
  It.  21, fac=  0.00195312, eval (no.,total): ( 1, 50): new dev = 310107
  It.  21, fac= 0.000976562, eval (no.,total): ( 2, 51): new dev = 310008
  It.  21, fac= 0.000488281, eval (no.,total): ( 3, 52): new dev = 309993
309992.8    (2.98e-01): par = (3092.052 152.3259 362.6423 25.53342 1.078699 1.334521 1.023995 3.528601 3.767606)
  It.  22, fac= 0.000976562, eval (no.,total): ( 1, 53): new dev = 310001
  It.  22, fac= 0.000488281, eval (no.,total): ( 2, 54): new dev = 309983
309983.2    (2.98e-01): par = (3275.571 152.3224 362.6503 27.15082 1.078644 1.334538 1.022686 3.529347 3.76752)
  It.  23, fac= 0.000976562, eval (no.,total): ( 1, 55): new dev = 309996
  It.  23, fac= 0.000488281, eval (no.,total): ( 2, 56): new dev = 309975
309974.9    (2.98e-01): par = (3482.599 152.3189 362.6583 28.97748 1.078589 1.334555 1.021375 3.530092 3.767434)
  It.  24, fac= 0.000976562, eval (no.,total): ( 1, 57): new dev = 309993
  It.  24, fac= 0.000488281, eval (no.,total): ( 2, 58): new dev = 309968
309967.9    (2.98e-01): par = (3717.838 152.3154 362.6662 31.05541 1.078534 1.334572 1.020062 3.530837 3.767347)
  It.  25, fac= 0.000976562, eval (no.,total): ( 1, 59): new dev = 309992
  It.  25, fac= 0.000488281, eval (no.,total): ( 2, 60): new dev = 309962
309962.5    (2.98e-01): par = (3987.306 152.3119 362.6742 33.4384 1.07848 1.334588 1.018749 3.531582 3.767261)
  It.  26, fac= 0.000976562, eval (no.,total): ( 1, 61): new dev = 309993
  It.  26, fac= 0.000488281, eval (no.,total): ( 2, 62): new dev = 309959
309958.8    (2.98e-01): par = (4298.832 152.3084 362.6822 36.19646 1.078425 1.334605 1.017434 3.532327 3.767175)
  It.  27, fac= 0.000976562, eval (no.,total): ( 1, 63): new dev = 309997
  It.  27, fac= 0.000488281, eval (no.,total): ( 2, 64): new dev = 309957
309957.3    (2.98e-01): par = (4662.764 152.3049 362.6901 39.42213 1.07837 1.334622 1.016118 3.533073 3.767089)
  It.  28, fac= 0.000976562, eval (no.,total): ( 1, 65): new dev = 310004
  It.  28, fac= 0.000488281, eval (no.,total): ( 2, 66): new dev = 309958
  It.  28, fac= 0.000244141, eval (no.,total): ( 3, 67): new dev = 309952
309951.6    (2.98e-01): par = (4877.901 152.3032 362.6941 41.33113 1.078343 1.334631 1.015459 3.533445 3.767046)
  It.  29, fac= 0.000488281, eval (no.,total): ( 1, 68): new dev = 309954
  It.  29, fac= 0.000244141, eval (no.,total): ( 2, 69): new dev = 309946
309946.3    (2.98e-01): par = (5113.992 152.3015 362.6981 43.42724 1.078316 1.334639 1.0148 3.533818 3.767002)
  It.  30, fac= 0.000488281, eval (no.,total): ( 1, 70): new dev = 309950
  It.  30, fac= 0.000244141, eval (no.,total): ( 2, 71): new dev = 309941
309941.4    (2.98e-01): par = (5374.188 152.2997 362.7021 45.73867 1.078288 1.334647 1.014141 3.53419 3.766959)
  It.  31, fac= 0.000488281, eval (no.,total): ( 1, 72): new dev = 309947
  It.  31, fac= 0.000244141, eval (no.,total): ( 2, 73): new dev = 309937
      309937. (2.98e-01): par = (5662.305 152.298 362.706 48.29958 1.078261 1.334656 1.013482 3.534563 3.766916)
  It.  32, fac= 0.000488281, eval (no.,total): ( 1, 74): new dev = 309945
  It.  32, fac= 0.000244141, eval (no.,total): ( 2, 75): new dev = 309933
309933.1    (2.98e-01): par = (5982.999 152.2963 362.71 51.15164 1.078234 1.334664 1.012822 3.534936 3.766873)
  It.  33, fac= 0.000488281, eval (no.,total): ( 1, 76): new dev = 309943
  It.  33, fac= 0.000244141, eval (no.,total): ( 2, 77): new dev = 309930
309929.8    (2.98e-01): par = (6341.996 152.2945 362.714 54.34611 1.078206 1.334673 1.012161 3.535308 3.76683)
  It.  34, fac= 0.000488281, eval (no.,total): ( 1, 78): new dev = 309942
  It.  34, fac= 0.000244141, eval (no.,total): ( 2, 79): new dev = 309927
309927.2    (2.98e-01): par = (6746.428 152.2928 362.718 57.94685 1.078179 1.334681 1.011501 3.535681 3.766787)
  It.  35, fac= 0.000488281, eval (no.,total): ( 1, 80): new dev = 309942
  It.  35, fac= 0.000244141, eval (no.,total): ( 2, 81): new dev = 309925
309925.3    (2.98e-01): par = (7205.281 152.291 362.7219 62.03436 1.078152 1.33469 1.01084 3.536053 3.766744)
  It.  36, fac= 0.000488281, eval (no.,total): ( 1, 82): new dev = 309943
  It.  36, fac= 0.000244141, eval (no.,total): ( 2, 83): new dev = 309924
309924.2    (2.98e-01): par = (7730.023 152.2893 362.7259 66.71134 1.078125 1.334698 1.010179 3.536426 3.766701)
  It.  37, fac= 0.000488281, eval (no.,total): ( 1, 84): new dev = 309946
  It.  37, fac= 0.000244141, eval (no.,total): ( 2, 85): new dev = 309924
309924.2    (2.98e-01): par = (8335.502 152.2876 362.7299 72.11081 1.078097 1.334706 1.009517 3.536798 3.766659)
  It.  38, fac= 0.000488281, eval (no.,total): ( 1, 86): new dev = 309950
  It.  38, fac= 0.000244141, eval (no.,total): ( 2, 87): new dev = 309925
  It.  38, fac=  0.00012207, eval (no.,total): ( 3, 88): new dev = 309921
309921.5    (2.98e-01): par = (8688.407 152.2867 362.7319 75.25956 1.078084 1.334711 1.009186 3.536984 3.766637)
  It.  39, fac= 0.000244141, eval (no.,total): ( 1, 89): new dev = 309923
  It.  39, fac=  0.00012207, eval (no.,total): ( 2, 90): new dev = 309919
      309919. (2.98e-01): par = (9072.362 152.2858 362.7338 78.68627 1.07807 1.334715 1.008855 3.537171 3.766616)
  It.  40, fac= 0.000244141, eval (no.,total): ( 1, 91): new dev = 309921
  It.  40, fac=  0.00012207, eval (no.,total): ( 2, 92): new dev = 309917
309916.6    (2.98e-01): par = (9491.583 152.285 362.7358 82.42868 1.078057 1.334719 1.008524 3.537357 3.766594)
  It.  41, fac= 0.000244141, eval (no.,total): ( 1, 93): new dev = 309920
  It.  41, fac=  0.00012207, eval (no.,total): ( 2, 94): new dev = 309914
309914.5    (2.98e-01): par = (9951.05 152.2841 362.7378 86.53143 1.078043 1.334723 1.008193 3.537543 3.766573)
  It.  42, fac= 0.000244141, eval (no.,total): ( 1, 95): new dev = 309919
  It.  42, fac=  0.00012207, eval (no.,total): ( 2, 96): new dev = 309913
309912.6    (2.98e-01): par = (10456.76 152.2833 362.7398 91.04827 1.078029 1.334727 1.007862 3.53773 3.766551)
  It.  43, fac= 0.000244141, eval (no.,total): ( 1, 97): new dev = 309918
  It.  43, fac=  0.00012207, eval (no.,total): ( 2, 98): new dev = 309911
      309911. (2.98e-01): par = (11015.93 152.2824 362.7418 96.04385 1.078016 1.334732 1.00753 3.537916 3.76653)
  It.  44, fac= 0.000244141, eval (no.,total): ( 1, 99): new dev = 309917
  It.  44, fac=  0.00012207, eval (no.,total): ( 2,100): new dev = 309910
309909.6    (2.98e-01): par = (11637.35 152.2815 362.7438 101.5969 1.078002 1.334736 1.007199 3.538102 3.766508)
  It.  45, fac= 0.000244141, eval (no.,total): ( 1,101): new dev = 309917
  It.  45, fac=  0.00012207, eval (no.,total): ( 2,102): new dev = 309909
309908.6    (2.98e-01): par = (12331.77 152.2807 362.7458 107.8038 1.077989 1.33474 1.006867 3.538288 3.766487)
  It.  46, fac= 0.000244141, eval (no.,total): ( 1,103): new dev = 309917
  It.  46, fac=  0.00012207, eval (no.,total): ( 2,104): new dev = 309908
309907.9    (2.98e-01): par = (13112.58 152.2798 362.7477 114.7845 1.077975 1.334744 1.006536 3.538475 3.766465)
  It.  47, fac= 0.000244141, eval (no.,total): ( 1,105): new dev = 309918
  It.  47, fac=  0.00012207, eval (no.,total): ( 2,106): new dev = 309908
309907.6    (2.98e-01): par = (13996.52 152.2789 362.7497 122.6891 1.077961 1.334748 1.006204 3.538661 3.766444)
  It.  48, fac= 0.000244141, eval (no.,total): ( 1,107): new dev = 309919
  It.  48, fac=  0.00012207, eval (no.,total): ( 2,108): new dev = 309908
  It.  48, fac= 6.10352e-05, eval (no.,total): ( 3,109): new dev = 309906
309906.1    (2.98e-01): par = (14500.73 152.2785 362.7507 127.1991 1.077955 1.334751 1.006038 3.538754 3.766433)
  It.  49, fac=  0.00012207, eval (no.,total): ( 1,110): new dev = 309907
  It.  49, fac= 6.10352e-05, eval (no.,total): ( 2,111): new dev = 309905
309904.7    (2.98e-01): par = (15042.3 152.2781 362.7517 132.0437 1.077948 1.334753 1.005872 3.538847 3.766422)
  It.  50, fac=  0.00012207, eval (no.,total): ( 1,112): new dev = 309905
  It.  50, fac= 6.10352e-05, eval (no.,total): ( 2,113): new dev = 309903
309903.4    (2.98e-01): par = (15625.48 152.2776 362.7527 137.2612 1.077941 1.334755 1.005706 3.53894 3.766412)
  It.  51, fac=  0.00012207, eval (no.,total): ( 1,114): new dev = 309904
  It.  51, fac= 6.10352e-05, eval (no.,total): ( 2,115): new dev = 309902
309902.2    (2.98e-01): par = (16255.2 152.2772 362.7537 142.8956 1.077934 1.334757 1.00554 3.539033 3.766401)
  It.  52, fac=  0.00012207, eval (no.,total): ( 1,116): new dev = 309903
  It.  52, fac= 6.10352e-05, eval (no.,total): ( 2,117): new dev = 309901
309901.0    (2.98e-01): par = (16937.16 152.2768 362.7547 148.998 1.077928 1.334759 1.005375 3.539126 3.76639)
  It.  53, fac=  0.00012207, eval (no.,total): ( 1,118): new dev = 309903
  It.  53, fac= 6.10352e-05, eval (no.,total): ( 2,119): new dev = 309900
      309900. (2.98e-01): par = (17678.05 152.2763 362.7557 155.6285 1.077921 1.334761 1.005209 3.53922 3.76638)
  It.  54, fac=  0.00012207, eval (no.,total): ( 1,120): new dev = 309902
  It.  54, fac= 6.10352e-05, eval (no.,total): ( 2,121): new dev = 309899
      309899. (2.98e-01): par = (18485.74 152.2759 362.7567 162.8575 1.077914 1.334763 1.005043 3.539313 3.766369)
  It.  55, fac=  0.00012207, eval (no.,total): ( 1,122): new dev = 309901
  It.  55, fac= 6.10352e-05, eval (no.,total): ( 2,123): new dev = 309898
309898.1    (2.98e-01): par = (19369.49 152.2755 362.7576 170.768 1.077907 1.334765 1.004877 3.539406 3.766358)
  It.  56, fac=  0.00012207, eval (no.,total): ( 1,124): new dev = 309901
  It.  56, fac= 6.10352e-05, eval (no.,total): ( 2,125): new dev = 309897
309897.4    (2.98e-01): par = (20340.44 152.275 362.7586 179.46 1.0779 1.334767 1.00471 3.539499 3.766347)
  It.  57, fac=  0.00012207, eval (no.,total): ( 1,126): new dev = 309901
  It.  57, fac= 6.10352e-05, eval (no.,total): ( 2,127): new dev = 309897
309896.8    (2.98e-01): par = (21411.95 152.2746 362.7596 189.0529 1.077894 1.334769 1.004544 3.539592 3.766337)
  It.  58, fac=  0.00012207, eval (no.,total): ( 1,128): new dev = 309901
  It.  58, fac= 6.10352e-05, eval (no.,total): ( 2,129): new dev = 309896
309896.3    (2.98e-01): par = (22600.07 152.2742 362.7606 199.6909 1.077887 1.334772 1.004378 3.539685 3.766326)
  It.  59, fac=  0.00012207, eval (no.,total): ( 1,130): new dev = 309901
  It.  59, fac= 6.10352e-05, eval (no.,total): ( 2,131): new dev = 309896
309896.0    (2.98e-01): par = (23924.57 152.2737 362.7616 211.5508 1.07788 1.334774 1.004212 3.539778 3.766315)
  It.  60, fac=  0.00012207, eval (no.,total): ( 1,132): new dev = 309901
  It.  60, fac= 6.10352e-05, eval (no.,total): ( 2,133): new dev = 309896
309895.9    (2.98e-01): par = (25409.83 152.2733 362.7626 224.8514 1.077873 1.334776 1.004046 3.539871 3.766305)
  It.  61, fac=  0.00012207, eval (no.,total): ( 1,134): new dev = 309902
  It.  61, fac= 6.10352e-05, eval (no.,total): ( 2,135): new dev = 309896
  It.  61, fac= 3.05176e-05, eval (no.,total): ( 3,136): new dev = 309895
309895.2    (2.98e-01): par = (26248.05 152.2731 362.7631 232.3583 1.07787 1.334777 1.003963 3.539918 3.766299)
  It.  62, fac= 6.10352e-05, eval (no.,total): ( 1,137): new dev = 309895
  It.  62, fac= 3.05176e-05, eval (no.,total): ( 2,138): new dev = 309894
309894.5    (2.98e-01): par = (27142.84 152.2729 362.7636 240.3721 1.077866 1.334778 1.00388 3.539964 3.766294)
  It.  63, fac= 6.10352e-05, eval (no.,total): ( 1,139): new dev = 309895
  It.  63, fac= 3.05176e-05, eval (no.,total): ( 2,140): new dev = 309894
309893.8    (2.98e-01): par = (28100.01 152.2727 362.7641 248.9448 1.077863 1.334779 1.003797 3.540011 3.766288)
  It.  64, fac= 6.10352e-05, eval (no.,total): ( 1,141): new dev = 309894
  It.  64, fac= 3.05176e-05, eval (no.,total): ( 2,142): new dev = 309893
309893.2    (2.98e-01): par = (29126.25 152.2725 362.7646 258.1365 1.07786 1.33478 1.003714 3.540058 3.766283)
  It.  65, fac= 6.10352e-05, eval (no.,total): ( 1,143): new dev = 309894
  It.  65, fac= 3.05176e-05, eval (no.,total): ( 2,144): new dev = 309893
309892.6    (2.98e-01): par = (30229.15 152.2722 362.7651 268.015 1.077856 1.334781 1.003631 3.540104 3.766278)
  It.  66, fac= 6.10352e-05, eval (no.,total): ( 1,145): new dev = 309893
  It.  66, fac= 3.05176e-05, eval (no.,total): ( 2,146): new dev = 309892
309892.0    (2.98e-01): par = (31417.57 152.272 362.7656 278.6598 1.077853 1.334782 1.003547 3.540151 3.766272)
  It.  67, fac= 6.10352e-05, eval (no.,total): ( 1,147): new dev = 309893
  It.  67, fac= 3.05176e-05, eval (no.,total): ( 2,148): new dev = 309892
309891.5    (2.98e-01): par = (32701.67 152.2718 362.7661 290.1619 1.077849 1.334783 1.003464 3.540197 3.766267)
  It.  68, fac= 6.10352e-05, eval (no.,total): ( 1,149): new dev = 309893
  It.  68, fac= 3.05176e-05, eval (no.,total): ( 2,150): new dev = 309891
309891.1    (2.98e-01): par = (34093.37 152.2716 362.7666 302.6282 1.077846 1.334784 1.003381 3.540244 3.766262)
  It.  69, fac= 6.10352e-05, eval (no.,total): ( 1,151): new dev = 309892
  It.  69, fac= 3.05176e-05, eval (no.,total): ( 2,152): new dev = 309891
309890.6    (2.98e-01): par = (35606.7 152.2714 362.7671 316.1842 1.077843 1.334785 1.003298 3.54029 3.766256)
  It.  70, fac= 6.10352e-05, eval (no.,total): ( 1,153): new dev = 309892
  It.  70, fac= 3.05176e-05, eval (no.,total): ( 2,154): new dev = 309890
309890.3    (2.98e-01): par = (37257.96 152.2712 362.7676 330.9761 1.077839 1.334786 1.003215 3.540337 3.766251)
  It.  71, fac= 6.10352e-05, eval (no.,total): ( 1,155): new dev = 309892
  It.  71, fac= 3.05176e-05, eval (no.,total): ( 2,156): new dev = 309890
      309890. (2.98e-01): par = (39066.42 152.2709 362.768 347.1764 1.077836 1.334787 1.003132 3.540384 3.766246)
  It.  72, fac= 6.10352e-05, eval (no.,total): ( 1,157): new dev = 309892
  It.  72, fac= 3.05176e-05, eval (no.,total): ( 2,158): new dev = 309890
309889.7    (2.98e-01): par = (41055.42 152.2707 362.7685 364.9942 1.077832 1.334788 1.003049 3.54043 3.76624)
  It.  73, fac= 6.10352e-05, eval (no.,total): ( 1,159): new dev = 309892
  It.  73, fac= 3.05176e-05, eval (no.,total): ( 2,160): new dev = 309890
309889.5    (2.98e-01): par = (43252.57 152.2705 362.769 384.6769 1.077829 1.334789 1.002966 3.540477 3.766235)
  It.  74, fac= 6.10352e-05, eval (no.,total): ( 1,161): new dev = 309892
  It.  74, fac= 3.05176e-05, eval (no.,total): ( 2,162): new dev = 309889
309889.4    (2.98e-01): par = (45692.27 152.2703 362.7695 406.5326 1.077826 1.33479 1.002882 3.540523 3.76623)
  It.  75, fac= 6.10352e-05, eval (no.,total): ( 1,163): new dev = 309892
  It.  75, fac= 3.05176e-05, eval (no.,total): ( 2,164): new dev = 309889
309889.4    (2.98e-01): par = (48415.48 152.2701 362.77 430.9281 1.077822 1.334791 1.002799 3.54057 3.766224)
  It.  76, fac= 6.10352e-05, eval (no.,total): ( 1,165): new dev = 309892
  It.  76, fac= 3.05176e-05, eval (no.,total): ( 2,166): new dev = 309889
  It.  76, fac= 1.52588e-05, eval (no.,total): ( 3,167): new dev = 309889
309889.1    (2.98e-01): par = (49944.86 152.27 362.7703 444.6288 1.077821 1.334792 1.002758 3.540593 3.766222)
  It.  77, fac= 3.05176e-05, eval (no.,total): ( 1,168): new dev = 309889
  It.  77, fac= 1.52588e-05, eval (no.,total): ( 2,169): new dev = 309889
309888.7    (2.98e-01): par = (51572.64 152.2699 362.7705 459.211 1.077819 1.334792 1.002716 3.540616 3.766219)
  It.  78, fac= 3.05176e-05, eval (no.,total): ( 1,170): new dev = 309889
  It.  78, fac= 1.52588e-05, eval (no.,total): ( 2,171): new dev = 309888
309888.4    (2.98e-01): par = (53308.35 152.2698 362.7708 474.76 1.077817 1.334793 1.002674 3.54064 3.766216)
  It.  79, fac= 3.05176e-05, eval (no.,total): ( 1,172): new dev = 309889
  It.  79, fac= 1.52588e-05, eval (no.,total): ( 2,173): new dev = 309888
309888.1    (2.98e-01): par = (55163.44 152.2696 362.771 491.3783 1.077816 1.334794 1.002633 3.540663 3.766214)
  It.  80, fac= 3.05176e-05, eval (no.,total): ( 1,174): new dev = 309888
  It.  80, fac= 1.52588e-05, eval (no.,total): ( 2,175): new dev = 309888
309887.8    (2.98e-01): par = (57150.14 152.2695 362.7713 509.1754 1.077814 1.334794 1.002591 3.540686 3.766211)
  It.  81, fac= 3.05176e-05, eval (no.,total): ( 1,176): new dev = 309888
  It.  81, fac= 1.52588e-05, eval (no.,total): ( 2,177): new dev = 309887
309887.5    (2.98e-01): par = (59283.21 152.2694 362.7715 528.2835 1.077812 1.334795 1.00255 3.540709 3.766208)
  It.  82, fac= 3.05176e-05, eval (no.,total): ( 1,178): new dev = 309888
  It.  82, fac= 1.52588e-05, eval (no.,total): ( 2,179): new dev = 309887
309887.2    (2.98e-01): par = (61578.4 152.2693 362.7718 548.8437 1.07781 1.334795 1.002508 3.540733 3.766205)
  It.  83, fac= 3.05176e-05, eval (no.,total): ( 1,180): new dev = 309888
  It.  83, fac= 1.52588e-05, eval (no.,total): ( 2,181): new dev = 309887
309887.0    (2.98e-01): par = (64055.69 152.2692 362.772 571.0348 1.077809 1.334796 1.002467 3.540756 3.766203)
  It.  84, fac= 3.05176e-05, eval (no.,total): ( 1,182): new dev = 309888
  It.  84, fac= 1.52588e-05, eval (no.,total): ( 2,183): new dev = 309887
309886.8    (2.98e-01): par = (66736.28 152.2691 362.7723 595.0467 1.077807 1.334796 1.002425 3.540779 3.7662)
  It.  85, fac= 3.05176e-05, eval (no.,total): ( 1,184): new dev = 309887
  It.  85, fac= 1.52588e-05, eval (no.,total): ( 2,185): new dev = 309887
309886.6    (2.98e-01): par = (69646.47 152.269 362.7725 621.1148 1.077805 1.334797 1.002383 3.540803 3.766197)
  It.  86, fac= 3.05176e-05, eval (no.,total): ( 1,186): new dev = 309887
  It.  86, fac= 1.52588e-05, eval (no.,total): ( 2,187): new dev = 309886
309886.4    (2.98e-01): par = (72817.15 152.2689 362.7728 649.5156 1.077804 1.334797 1.002342 3.540826 3.766195)
  It.  87, fac= 3.05176e-05, eval (no.,total): ( 1,188): new dev = 309887
  It.  87, fac= 1.52588e-05, eval (no.,total): ( 2,189): new dev = 309886
309886.3    (2.98e-01): par = (76282.1 152.2688 362.773 680.5516 1.077802 1.334798 1.0023 3.540849 3.766192)
  It.  88, fac= 3.05176e-05, eval (no.,total): ( 1,190): new dev = 309887
  It.  88, fac= 1.52588e-05, eval (no.,total): ( 2,191): new dev = 309886
309886.2    (2.98e-01): par = (80086.11 152.2687 362.7732 714.6238 1.0778 1.334798 1.002259 3.540872 3.766189)
  It.  89, fac= 3.05176e-05, eval (no.,total): ( 1,192): new dev = 309887
  It.  89, fac= 1.52588e-05, eval (no.,total): ( 2,193): new dev = 309886
309886.1    (2.98e-01): par = (84279.76 152.2686 362.7735 752.1848 1.077799 1.334799 1.002217 3.540896 3.766187)
  It.  90, fac= 3.05176e-05, eval (no.,total): ( 1,194): new dev = 309887
  It.  90, fac= 1.52588e-05, eval (no.,total): ( 2,195): new dev = 309886
309886.1    (2.98e-01): par = (88924.4 152.2685 362.7737 793.7838 1.077797 1.334799 1.002175 3.540919 3.766184)
  It.  91, fac= 3.05176e-05, eval (no.,total): ( 1,196): new dev = 309887
  It.  91, fac= 1.52588e-05, eval (no.,total): ( 2,197): new dev = 309886
309886.1    (2.98e-01): par = (94096.26 152.2684 362.774 840.1033 1.077795 1.3348 1.002134 3.540942 3.766181)
  It.  92, fac= 3.05176e-05, eval (no.,total): ( 1,198): new dev = 309888
  It.  92, fac= 1.52588e-05, eval (no.,total): ( 2,199): new dev = 309886
  It.  92, fac= 7.62939e-06, eval (no.,total): ( 3,200): new dev = 309886
309885.9    (2.98e-01): par = (96992.84 152.2683 362.7741 866.0442 1.077794 1.3348 1.002113 3.540954 3.76618)
  It.  93, fac= 1.52588e-05, eval (no.,total): ( 1,201): new dev = 309886
  It.  93, fac= 7.62939e-06, eval (no.,total): ( 2,202): new dev = 309886
309885.7    (2.98e-01): par = (100070.8 152.2682 362.7742 893.6084 1.077793 1.3348 1.002092 3.540966 3.766179)
  It.  94, fac= 1.52588e-05, eval (no.,total): ( 1,203): new dev = 309886
  It.  94, fac= 7.62939e-06, eval (no.,total): ( 2,204): new dev = 309886
309885.5    (2.98e-01): par = (103347.2 152.2682 362.7744 922.9499 1.077793 1.334801 1.002071 3.540977 3.766177)
  It.  95, fac= 1.52588e-05, eval (no.,total): ( 1,205): new dev = 309886
  It.  95, fac= 7.62939e-06, eval (no.,total): ( 2,206): new dev = 309885
309885.4    (2.98e-01): par = (106841.9 152.2681 362.7745 954.2448 1.077792 1.334801 1.002051 3.540989 3.766176)
  It.  96, fac= 1.52588e-05, eval (no.,total): ( 1,207): new dev = 309886
  It.  96, fac= 7.62939e-06, eval (no.,total): ( 2,208): new dev = 309885
309885.2    (2.98e-01): par = (110577.1 152.2681 362.7746 987.6932 1.077791 1.334801 1.00203 3.541 3.766175)
  It.  97, fac= 1.52588e-05, eval (no.,total): ( 1,209): new dev = 309885
  It.  97, fac= 7.62939e-06, eval (no.,total): ( 2,210): new dev = 309885
309885.1    (2.98e-01): par = (114578.7 152.268 362.7747 1023.525 1.07779 1.334801 1.002009 3.541012 3.766173)
  It.  98, fac= 1.52588e-05, eval (no.,total): ( 1,211): new dev = 309885
  It.  98, fac= 7.62939e-06, eval (no.,total): ( 2,212): new dev = 309885
      309885. (2.98e-01): par = (118875.6 152.268 362.7749 1062.001 1.077789 1.334802 1.001988 3.541024 3.766172)
  It.  99, fac= 1.52588e-05, eval (no.,total): ( 1,213): new dev = 309885
  It.  99, fac= 7.62939e-06, eval (no.,total): ( 2,214): new dev = 309885
309884.8    (2.98e-01): par = (123501.3 152.2679 362.775 1103.42 1.077788 1.334802 1.001967 3.541035 3.766171)
  It. 100, fac= 1.52588e-05, eval (no.,total): ( 1,215): new dev = 309885
  It. 100, fac= 7.62939e-06, eval (no.,total): ( 2,216): new dev = 309885
309884.7    (2.98e-01): par = (128493.8 152.2679 362.7751 1148.121 1.077788 1.334802 1.001947 3.541047 3.766169)
  It. 101, fac= 1.52588e-05, eval (no.,total): ( 1,217): new dev = 309885
  It. 101, fac= 7.62939e-06, eval (no.,total): ( 2,218): new dev = 309885
309884.6    (2.98e-01): par = (133898 152.2678 362.7752 1196.507 1.077787 1.334802 1.001926 3.541059 3.766168)
  It. 102, fac= 1.52588e-05, eval (no.,total): ( 1,219): new dev = 309885
  It. 102, fac= 7.62939e-06, eval (no.,total): ( 2,220): new dev = 309885
309884.5    (2.98e-01): par = (139769.5 152.2678 362.7754 1249.074 1.077786 1.334803 1.001905 3.54107 3.766167)
  It. 103, fac= 1.52588e-05, eval (no.,total): ( 1,221): new dev = 309885
  It. 103, fac= 7.62939e-06, eval (no.,total): ( 2,222): new dev = 309884
309884.4    (2.98e-01): par = (146167.6 152.2677 362.7755 1306.354 1.077785 1.334803 1.001884 3.541082 3.766165)
  It. 104, fac= 1.52588e-05, eval (no.,total): ( 1,223): new dev = 309885
  It. 104, fac= 7.62939e-06, eval (no.,total): ( 2,224): new dev = 309884
309884.3    (2.98e-01): par = (153164.7 152.2677 362.7756 1368.995 1.077784 1.334803 1.001863 3.541094 3.766164)
  It. 105, fac= 1.52588e-05, eval (no.,total): ( 1,225): new dev = 309885
  It. 105, fac= 7.62939e-06, eval (no.,total): ( 2,226): new dev = 309884
309884.3    (2.98e-01): par = (160849.5 152.2676 362.7757 1437.788 1.077783 1.334804 1.001843 3.541105 3.766163)
  It. 106, fac= 1.52588e-05, eval (no.,total): ( 1,227): new dev = 309885
  It. 106, fac= 7.62939e-06, eval (no.,total): ( 2,228): new dev = 309884
309884.2    (2.98e-01): par = (169321.1 152.2675 362.7758 1513.62 1.077782 1.334804 1.001822 3.541117 3.766161)
  It. 107, fac= 1.52588e-05, eval (no.,total): ( 1,229): new dev = 309885
  It. 107, fac= 7.62939e-06, eval (no.,total): ( 2,230): new dev = 309884
309884.2    (2.98e-01): par = (178712.6 152.2675 362.776 1597.683 1.077782 1.334804 1.001801 3.541128 3.76616)
  It. 108, fac= 1.52588e-05, eval (no.,total): ( 1,231): new dev = 309885
  It. 108, fac= 7.62939e-06, eval (no.,total): ( 2,232): new dev = 309884
309884.2    (2.98e-01): par = (189175.5 152.2674 362.7761 1691.332 1.077781 1.334804 1.00178 3.54114 3.766159)
  It. 109, fac= 1.52588e-05, eval (no.,total): ( 1,233): new dev = 309885
  It. 109, fac= 7.62939e-06, eval (no.,total): ( 2,234): new dev = 309884
  It. 109, fac=  3.8147e-06, eval (no.,total): ( 3,235): new dev = 309884
309884.1    (2.98e-01): par = (195034.1 152.2674 362.7762 1743.766 1.07778 1.334804 1.00177 3.541146 3.766158)
  It. 110, fac= 7.62939e-06, eval (no.,total): ( 1,236): new dev = 309884
  It. 110, fac=  3.8147e-06, eval (no.,total): ( 2,237): new dev = 309884
309884.0    (2.98e-01): par = (201264.5 152.2674 362.7762 1799.526 1.07778 1.334805 1.001759 3.541152 3.766157)
  It. 111, fac= 7.62939e-06, eval (no.,total): ( 1,238): new dev = 309884
  It. 111, fac=  3.8147e-06, eval (no.,total): ( 2,239): new dev = 309884
309883.9    (2.98e-01): par = (207898.8 152.2674 362.7763 1858.898 1.07778 1.334805 1.001749 3.541158 3.766157)
  It. 112, fac= 7.62939e-06, eval (no.,total): ( 1,240): new dev = 309884
  It. 112, fac=  3.8147e-06, eval (no.,total): ( 2,241): new dev = 309884
309883.8    (2.98e-01): par = (214982.6 152.2673 362.7763 1922.291 1.077779 1.334805 1.001739 3.541163 3.766156)
  It. 113, fac= 7.62939e-06, eval (no.,total): ( 1,242): new dev = 309884
  It. 113, fac=  3.8147e-06, eval (no.,total): ( 2,243): new dev = 309884
309883.7    (2.98e-01): par = (222554.4 152.2673 362.7764 1990.049 1.077779 1.334805 1.001728 3.541169 3.766155)
  It. 114, fac= 7.62939e-06, eval (no.,total): ( 1,244): new dev = 309884
  It. 114, fac=  3.8147e-06, eval (no.,total): ( 2,245): new dev = 309884
309883.7    (2.98e-01): par = (230670 152.2673 362.7765 2062.669 1.077778 1.334805 1.001718 3.541175 3.766155)
  It. 115, fac= 7.62939e-06, eval (no.,total): ( 1,246): new dev = 309884
  It. 115, fac=  3.8147e-06, eval (no.,total): ( 2,247): new dev = 309884
309883.6    (2.98e-01): par = (239388.3 152.2673 362.7765 2140.681 1.077778 1.334805 1.001707 3.541181 3.766154)
  It. 116, fac= 7.62939e-06, eval (no.,total): ( 1,248): new dev = 309884
  It. 116, fac=  3.8147e-06, eval (no.,total): ( 2,249): new dev = 309884
309883.5    (2.98e-01): par = (248780.9 152.2672 362.7766 2224.721 1.077777 1.334805 1.001697 3.541187 3.766153)
  It. 117, fac= 7.62939e-06, eval (no.,total): ( 1,250): new dev = 309884
  It. 117, fac=  3.8147e-06, eval (no.,total): ( 2,251): new dev = 309883
309883.4    (2.98e-01): par = (258918.9 152.2672 362.7767 2315.428 1.077777 1.334805 1.001686 3.541192 3.766153)
  It. 118, fac= 7.62939e-06, eval (no.,total): ( 1,252): new dev = 309884
  It. 118, fac=  3.8147e-06, eval (no.,total): ( 2,253): new dev = 309883
309883.4    (2.98e-01): par = (269901.6 152.2672 362.7767 2413.688 1.077777 1.334806 1.001676 3.541198 3.766152)
  It. 119, fac= 7.62939e-06, eval (no.,total): ( 1,254): new dev = 309883
  It. 119, fac=  3.8147e-06, eval (no.,total): ( 2,255): new dev = 309883
309883.3    (2.98e-01): par = (281837.1 152.2671 362.7768 2520.467 1.077776 1.334806 1.001666 3.541204 3.766151)
  It. 120, fac= 7.62939e-06, eval (no.,total): ( 1,256): new dev = 309883
  It. 120, fac=  3.8147e-06, eval (no.,total): ( 2,257): new dev = 309883
309883.2    (2.98e-01): par = (294849.8 152.2671 362.7768 2636.878 1.077776 1.334806 1.001655 3.54121 3.766151)
  It. 121, fac= 7.62939e-06, eval (no.,total): ( 1,258): new dev = 309883
  It. 121, fac=  3.8147e-06, eval (no.,total): ( 2,259): new dev = 309883
309883.2    (2.98e-01): par = (309084 152.2671 362.7769 2764.208 1.077775 1.334806 1.001645 3.541216 3.76615)
  It. 122, fac= 7.62939e-06, eval (no.,total): ( 1,260): new dev = 309883
  It. 122, fac=  3.8147e-06, eval (no.,total): ( 2,261): new dev = 309883
309883.1    (2.98e-01): par = (324726.8 152.2671 362.777 2904.132 1.077775 1.334806 1.001634 3.541222 3.766149)
  It. 123, fac= 7.62939e-06, eval (no.,total): ( 1,262): new dev = 309883
  It. 123, fac=  3.8147e-06, eval (no.,total): ( 2,263): new dev = 309883
309883.1    (2.98e-01): par = (341996.1 152.267 362.777 3058.595 1.077774 1.334806 1.001624 3.541227 3.766149)
  It. 124, fac= 7.62939e-06, eval (no.,total): ( 1,264): new dev = 309883
  It. 124, fac=  3.8147e-06, eval (no.,total): ( 2,265): new dev = 309883
309883.0    (2.98e-01): par = (361165.6 152.267 362.7771 3230.043 1.077774 1.334806 1.001614 3.541233 3.766148)
  It. 125, fac= 7.62939e-06, eval (no.,total): ( 1,266): new dev = 309883
  It. 125, fac=  3.8147e-06, eval (no.,total): ( 2,267): new dev = 309883
      309883. (2.98e-01): par = (382537.6 152.267 362.7771 3421.178 1.077774 1.334807 1.001603 3.541239 3.766147)
  It. 126, fac= 7.62939e-06, eval (no.,total): ( 1,268): new dev = 309883
  It. 126, fac=  3.8147e-06, eval (no.,total): ( 2,269): new dev = 309883
309882.9    (2.98e-01): par = (406509.7 152.267 362.7772 3635.551 1.077773 1.334807 1.001593 3.541245 3.766147)
  It. 127, fac= 7.62939e-06, eval (no.,total): ( 1,270): new dev = 309883
  It. 127, fac=  3.8147e-06, eval (no.,total): ( 2,271): new dev = 309883
309882.9    (2.98e-01): par = (433600.8 152.2669 362.7773 3877.798 1.077773 1.334807 1.001582 3.541251 3.766146)
  It. 128, fac= 7.62939e-06, eval (no.,total): ( 1,272): new dev = 309883
  It. 128, fac=  3.8147e-06, eval (no.,total): ( 2,273): new dev = 309883
309882.9    (2.98e-01): par = (464430.6 152.2669 362.7773 4153.455 1.077772 1.334807 1.001572 3.541256 3.766145)
  It. 129, fac= 7.62939e-06, eval (no.,total): ( 1,274): new dev = 309883
  It. 129, fac=  3.8147e-06, eval (no.,total): ( 2,275): new dev = 309883
309882.8    (2.98e-01): par = (499759.3 152.2669 362.7774 4469.31 1.077772 1.334807 1.001562 3.541262 3.766145)
  It. 130, fac= 7.62939e-06, eval (no.,total): ( 1,276): new dev = 309883
  It. 130, fac=  3.8147e-06, eval (no.,total): ( 2,277): new dev = 309883
309882.8    (2.98e-01): par = (540665.4 152.2668 362.7775 4834.995 1.077771 1.334807 1.001551 3.541268 3.766144)
  It. 131, fac= 7.62939e-06, eval (no.,total): ( 1,278): new dev = 309883
  It. 131, fac=  3.8147e-06, eval (no.,total): ( 2,279): new dev = 309883
309882.8    (2.98e-01): par = (588638.3 152.2668 362.7775 5263.814 1.077771 1.334807 1.001541 3.541274 3.766143)
  It. 132, fac= 7.62939e-06, eval (no.,total): ( 1,280): new dev = 309883
  It. 132, fac=  3.8147e-06, eval (no.,total): ( 2,281): new dev = 309883
309882.7    (2.98e-01): par = (645470.7 152.2668 362.7776 5771.771 1.077771 1.334807 1.00153 3.54128 3.766143)
  It. 133, fac= 7.62939e-06, eval (no.,total): ( 1,282): new dev = 309883
  It. 133, fac=  3.8147e-06, eval (no.,total): ( 2,283): new dev = 309883
309882.6    (2.98e-01): par = (713841.8 152.2668 362.7776 6382.789 1.07777 1.334808 1.00152 3.541286 3.766142)
  It. 134, fac= 7.62939e-06, eval (no.,total): ( 1,284): new dev = 309883
  It. 134, fac=  3.8147e-06, eval (no.,total): ( 2,285): new dev = 309883
309882.6    (2.98e-01): par = (797515.2 152.2667 362.7777 7130.465 1.07777 1.334808 1.00151 3.541291 3.766141)
  It. 135, fac= 7.62939e-06, eval (no.,total): ( 1,286): new dev = 309883
309882.6    (2.98e-01): par = (1005915 152.2667 362.7778 8992.392 1.077769 1.334808 1.001489 3.541303 3.76614)
  It. 136, fac= 1.52588e-05, eval (no.,total): ( 1,287): new dev = 309883
  It. 136, fac= 7.62939e-06, eval (no.,total): ( 2,288): new dev = 309882
309882.2    (2.98e-01): par = (1337440 152.2666 362.778 11953.55 1.077768 1.334808 1.001468 3.541315 3.766139)
  It. 137, fac= 1.52588e-05, eval (no.,total): ( 1,289): new dev = 309880
309880.4    (2.98e-01): par = (2512055 152.2665 362.7782 22441.6 1.077766 1.334809 1.001426 3.541338 3.766136)
  It. 138, fac= 3.05176e-05, eval (no.,total): ( 1,290): new dev = 309869
309869.2    (2.97e-01): par = (10830147 152.2663 362.7787 96666.57 1.077763 1.33481 1.001343 3.541385 3.766131)
  It. 139, fac= 6.10352e-05, eval (no.,total): ( 1,291):Warning message:
In nls(Biom.2 ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage])),  :
  singular gradient
> ## "fails" but returns at least: singular gradient iteration 126
> m.c2
Nonlinear regression model
  model: Biom.2 ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage]))
   data: biomassTill
      Wm1       Wm2       Wm3        a1        a2        a3        b1        b2 
3.194e+08 1.523e+02 3.628e+02 2.848e+06 1.078e+00 1.335e+00 1.001e+00 3.541e+00 
       b3 
3.766e+00 
 residual sum-of-squares: 309829

Number of iterations till stop: 138 
Achieved convergence tolerance: 0.2974
Reason stopped: singular gradient
> 
> ## Robust: not converging in 20 steps (only warning)
> mrob <- nlrob(Biomass ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage])),
+               data = biomassTill, start = m00st, trace=TRUE)
robust iteration 1 
221630.5    (6.09e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
182287.8    (3.56e-01): par = (318.8886 282.024 311.2545 1.822548 1.494574 1.129525 2.41827 2.767964 3.476529)
163748.1    (1.10e-01): par = (318.805 288.0167 341.9654 1.786274 1.522607 1.353841 2.642103 2.802773 2.967205)
161787.5    (8.56e-03): par = (323.5734 289.8453 349.4942 1.808498 1.529869 1.364095 2.623699 2.785542 3.394001)
161775.6    (2.26e-04): par = (323.3195 289.595 349.5757 1.807366 1.528734 1.361839 2.626092 2.789592 3.442828)
161775.6    (3.08e-05): par = (323.4009 289.68 349.5981 1.80769 1.529108 1.361903 2.625694 2.788483 3.443476)
161775.6    (7.96e-06): par = (323.3889 289.659 349.5978 1.807642 1.529015 1.361902 2.625755 2.78877 3.443488)
 --> irls.delta(previous, resid) = 0.408764 -- *not* converged
robust iteration 2 
117522.1    (1.05e-01): par = (323.3889 289.659 349.5978 1.807642 1.529015 1.361902 2.625755 2.78877 3.443488)
116317.6    (3.00e-02): par = (309.8399 261.4694 339.9658 1.757397 1.458788 1.296644 2.681645 2.910159 3.869811)
116214.1    (1.55e-03): par = (312.0578 264.5256 344.209 1.765736 1.468128 1.311145 2.674374 2.896012 3.888938)
116213.8    (1.16e-04): par = (311.9484 264.5546 344.0997 1.765259 1.468147 1.310422 2.675235 2.897492 3.898021)
116213.8    (1.50e-05): par = (311.9696 264.5818 344.1002 1.765345 1.46828 1.310422 2.675113 2.897016 3.898588)
116213.8    (3.09e-06): par = (311.9668 264.5766 344.0999 1.765333 1.468254 1.31042 2.675129 2.897124 3.898638)
 --> irls.delta(previous, resid) = 0.0748333 -- *not* converged
robust iteration 3 
114540.4    (2.86e-02): par = (311.9668 264.5766 344.0999 1.765333 1.468254 1.31042 2.675129 2.897124 3.898638)
114446.9    (2.10e-03): par = (308.4384 262.4976 343.2871 1.75248 1.471376 1.297822 2.688719 2.878705 4.002375)
114446.4    (1.88e-04): par = (308.7768 262.2461 343.4617 1.753803 1.470158 1.298522 2.687043 2.88345 4.008064)
114446.4    (3.35e-05): par = (308.743 262.3038 343.4531 1.753664 1.470445 1.298481 2.687258 2.88232 4.008934)
114446.4    (7.62e-06): par = (308.7477 262.2903 343.4531 1.753683 1.470377 1.29848 2.687229 2.88259 4.009003)
 --> irls.delta(previous, resid) = 0.0199464 -- *not* converged
robust iteration 4 
114058.3    (8.86e-03): par = (308.7477 262.2903 343.4531 1.753683 1.470377 1.29848 2.687229 2.88259 4.009003)
114049.4    (6.10e-04): par = (306.7243 263.3887 343.2719 1.746941 1.478768 1.294858 2.692571 2.863133 4.035404)
114049.4    (1.14e-04): par = (306.8306 263.2693 343.2979 1.747354 1.478143 1.294968 2.691987 2.866724 4.036535)
114049.4    (2.70e-05): par = (306.8187 263.3239 343.2965 1.747305 1.478412 1.294961 2.692062 2.865754 4.036697)
114049.4    (6.53e-06): par = (306.8202 263.3119 343.2965 1.747312 1.478352 1.294961 2.692053 2.865985 4.036711)
 --> irls.delta(previous, resid) = 0.00614414 -- *not* converged
robust iteration 5 
113640.7    (3.53e-03): par = (306.8202 263.3119 343.2965 1.747312 1.478352 1.294961 2.692053 2.865985 4.036711)
113639.3    (2.12e-04): par = (304.7822 263.7971 343.188 1.740445 1.482136 1.293735 2.697783 2.858173 4.043971)
113639.3    (4.28e-05): par = (304.8944 263.7466 343.1959 1.740884 1.481876 1.293769 2.697154 2.859536 4.044165)
113639.3    (1.02e-05): par = (304.882 263.7673 343.1955 1.740833 1.481978 1.293767 2.697234 2.859171 4.0442)
113639.3    (2.49e-06): par = (304.8837 263.7626 343.1955 1.74084 1.481955 1.293767 2.697224 2.859259 4.044203)
 --> irls.delta(previous, resid) = 0.00251115 -- *not* converged
robust iteration 6 
113259.0    (2.04e-03): par = (304.8837 263.7626 343.1955 1.74084 1.481955 1.293767 2.697224 2.859259 4.044203)
113258.6    (7.80e-05): par = (302.9367 263.8221 343.1148 1.734292 1.483014 1.293296 2.702685 2.857353 4.04644)
113258.6    (1.18e-05): par = (303.0389 263.8116 343.1179 1.734694 1.48296 1.29331 2.702095 2.857649 4.046456)
113258.6    (2.43e-06): par = (303.0277 263.8162 343.1178 1.734647 1.482983 1.293309 2.70217 2.857569 4.046464)
 --> irls.delta(previous, resid) = 0.00153445 -- *not* converged
robust iteration 7 
113007.7    (1.69e-03): par = (303.0277 263.8162 343.1178 1.734647 1.482983 1.293309 2.70217 2.857569 4.046464)
113007.4    (4.79e-05): par = (301.3007 263.7487 343.0672 1.728976 1.483034 1.293115 2.706517 2.857682 4.04723)
113007.4    (5.68e-06): par = (301.3752 263.7523 343.0686 1.729269 1.483052 1.293121 2.706072 2.857629 4.04722)
 --> irls.delta(previous, resid) = 0.00131597 -- *not* converged
robust iteration 8 
112867.9    (1.60e-03): par = (301.3752 263.7523 343.0686 1.729269 1.483052 1.293121 2.706072 2.857629 4.04722)
112867.6    (3.77e-05): par = (299.8246 263.6773 343.0408 1.724307 1.482853 1.293039 2.709502 2.858166 4.047505)
112867.6    (5.23e-06): par = (299.8776 263.683 343.0414 1.724515 1.482881 1.293041 2.709173 2.858052 4.047497)
 --> irls.delta(previous, resid) = 0.00127036 -- *not* converged
robust iteration 9 
112799.9    (1.58e-03): par = (299.8776 263.683 343.0414 1.724515 1.482881 1.293041 2.709173 2.858052 4.047497)
112799.6    (2.96e-05): par = (298.4498 263.6301 343.0279 1.720046 1.482687 1.293007 2.711958 2.858526 4.047605)
112799.6    (4.12e-06): par = (298.4883 263.6347 343.0282 1.720195 1.48271 1.293008 2.711711 2.858431 4.0476)
 --> irls.delta(previous, resid) = 0.00126057 -- *not* converged
robust iteration 10 
112770.7    (1.58e-03): par = (298.4883 263.6347 343.0282 1.720195 1.48271 1.293008 2.711711 2.858431 4.0476)
112770.5    (2.42e-05): par = (297.1321 263.6041 343.0224 1.716005 1.48258 1.292994 2.71414 2.858737 4.04764)
112770.5    (3.05e-06): par = (297.1627 263.6069 343.0225 1.716123 1.482594 1.292995 2.713938 2.858677 4.047638)
 --> irls.delta(previous, resid) = 0.00125903 -- *not* converged
robust iteration 11 
112760.1    (1.58e-03): par = (297.1627 263.6069 343.0225 1.716123 1.482594 1.292995 2.713938 2.858677 4.047638)
112759.8    (2.14e-05): par = (295.8463 263.5914 343.0203 1.71208 1.482521 1.29299 2.716198 2.858845 4.047651)
112759.8    (2.42e-06): par = (295.873 263.5929 343.0203 1.712182 1.482528 1.29299 2.716018 2.858813 4.04765)
 --> irls.delta(previous, resid) = 0.00125948 -- *not* converged
robust iteration 12 
112757.3    (1.58e-03): par = (295.873 263.5929 343.0203 1.712182 1.482528 1.29299 2.716018 2.858813 4.04765)
112757.0    (2.03e-05): par = (294.5799 263.586 343.0197 1.708215 1.482492 1.292988 2.71821 2.858895 4.047653)
112757.0    (2.16e-06): par = (294.6046 263.5867 343.0197 1.708309 1.482496 1.292988 2.718039 2.858879 4.047653)
 --> irls.delta(previous, resid) = 0.00126039 -- *not* converged
robust iteration 13 
112757.3    (1.58e-03): par = (294.6046 263.5867 343.0197 1.708309 1.482496 1.292988 2.718039 2.858879 4.047653)
112757.1    (1.99e-05): par = (293.3269 263.5839 343.0196 1.704384 1.48248 1.292988 2.720209 2.858914 4.047653)
112757.1    (2.07e-06): par = (293.3507 263.5842 343.0196 1.704476 1.482481 1.292988 2.720042 2.858908 4.047653)
 --> irls.delta(previous, resid) = 0.00126137 -- *not* converged
robust iteration 14 
112758.1    (1.58e-03): par = (293.3507 263.5842 343.0196 1.704476 1.482481 1.292988 2.720042 2.858908 4.047653)
112757.8    (1.97e-05): par = (292.0851 263.5834 343.0197 1.700579 1.482475 1.292988 2.722211 2.85892 4.047652)
112757.8    (2.04e-06): par = (292.1083 263.5835 343.0197 1.700669 1.482476 1.292988 2.722045 2.858918 4.047652)
 --> irls.delta(previous, resid) = 0.0012623 -- *not* converged
robust iteration 15 
112758.9    (1.58e-03): par = (292.1083 263.5835 343.0197 1.700669 1.482476 1.292988 2.722045 2.858918 4.047652)
112758.6    (1.97e-05): par = (290.8536 263.5833 343.0198 1.696796 1.482474 1.292988 2.72422 2.858922 4.047652)
112758.6    (2.04e-06): par = (290.8765 263.5833 343.0198 1.696884 1.482474 1.292988 2.724054 2.858921 4.047652)
 --> irls.delta(previous, resid) = 0.00126316 -- *not* converged
robust iteration 16 
112759.6    (1.58e-03): par = (290.8765 263.5833 343.0198 1.696884 1.482474 1.292988 2.724054 2.858921 4.047652)
112759.3    (1.96e-05): par = (289.6324 263.5834 343.0198 1.693034 1.482474 1.292989 2.726237 2.858921 4.047652)
112759.3    (2.03e-06): par = (289.6549 263.5834 343.0198 1.693121 1.482474 1.292989 2.726072 2.858921 4.047652)
 --> irls.delta(previous, resid) = 0.00126394 -- *not* converged
robust iteration 17 
112760.1    (1.58e-03): par = (289.6549 263.5834 343.0198 1.693121 1.482474 1.292989 2.726072 2.858921 4.047652)
112759.8    (1.96e-05): par = (288.4213 263.5835 343.0199 1.689293 1.482474 1.292989 2.728263 2.858921 4.047651)
112759.8    (2.03e-06): par = (288.4434 263.5835 343.0199 1.689379 1.482474 1.292989 2.728097 2.858921 4.047651)
 --> irls.delta(previous, resid) = 0.00126464 -- *not* converged
robust iteration 18 
112760.5    (1.58e-03): par = (288.4434 263.5835 343.0199 1.689379 1.482474 1.292989 2.728097 2.858921 4.047651)
112760.2    (1.96e-05): par = (287.2204 263.5836 343.0199 1.685574 1.482474 1.292989 2.730295 2.85892 4.047651)
112760.2    (2.02e-06): par = (287.2421 263.5836 343.0199 1.685659 1.482474 1.292989 2.730129 2.85892 4.047651)
 --> irls.delta(previous, resid) = 0.00126527 -- *not* converged
robust iteration 19 
112760.9    (1.58e-03): par = (287.2421 263.5836 343.0199 1.685659 1.482474 1.292989 2.730129 2.85892 4.047651)
112760.6    (1.95e-05): par = (286.0295 263.5836 343.0199 1.681877 1.482475 1.292989 2.732334 2.85892 4.047651)
112760.6    (2.02e-06): par = (286.0509 263.5836 343.0199 1.68196 1.482475 1.292989 2.732169 2.85892 4.047651)
 --> irls.delta(previous, resid) = 0.00126582 -- *not* converged
robust iteration 20 
112761.2    (1.58e-03): par = (286.0509 263.5836 343.0199 1.68196 1.482475 1.292989 2.732169 2.85892 4.047651)
112760.9    (1.95e-05): par = (284.8488 263.5836 343.0199 1.678201 1.482475 1.292989 2.734381 2.85892 4.047651)
112760.9    (2.01e-06): par = (284.8698 263.5836 343.0199 1.678283 1.482475 1.292989 2.734215 2.85892 4.047651)
 --> irls.delta(previous, resid) = 0.0012663 -- *not* converged
Warning message:
In nlrob(Biomass ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage])),  :
  failed to converge in 20 steps
> stopifnot(identical(mrob$dataClasses,
+                     c(Biomass = "numeric", Tillage = "factor", DVS = "numeric")))
> try(## now: singular gradient in nls
+ mr.2 <- nlrob(Biom.2  ~ Wm[Tillage] * (-expm1(-(DVS/a[Tillage])^b[Tillage])),
+               data = biomassTill, start = m00st, trace=TRUE)
+ )
robust iteration 1 
254879.8    (6.42e-01): par = (300 300 300 1.5 1.5 1.5 2.2 2.2 2.2)
205968.0    (3.87e-01): par = (378.5169 187.1208 304.3391 1.987966 1.126072 1.302035 1.656035 2.712645 2.854579)
202969.7    (3.67e-01): par = (561.0957 185.1383 316.7028 2.992486 1.132649 1.322806 1.398006 2.90733 2.984323)
202028.3    (3.60e-01): par = (723.2085 184.7889 318.9273 3.884849 1.133846 1.325783 1.334008 2.947067 3.011013)
201425.8    (3.56e-01): par = (882.2615 184.6267 319.9639 4.742891 1.134403 1.327119 1.301686 2.965931 3.023689)
201143.5    (3.54e-01): par = (1142.369 184.4701 320.9654 6.118309 1.13494 1.328389 1.269096 2.984308 3.036041)
200842.6    (3.52e-01): par = (1381.272 184.3946 321.4494 7.35005 1.1352 1.328993 1.252659 2.993255 3.042058)
200622.7    (3.50e-01): par = (1749.189 184.3204 321.9252 9.205833 1.135454 1.329582 1.23612 3.002085 3.047996)
200482.1    (3.49e-01): par = (2370.243 184.2474 322.3931 12.254 1.135705 1.330156 1.219472 3.010797 3.053857)
200374.3    (3.48e-01): par = (3569.422 184.1757 322.8531 17.93768 1.135951 1.330716 1.202709 3.019393 3.059642)
200079.1    (3.46e-01): par = (6427.48 184.1052 323.3055 30.87733 1.136192 1.331263 1.185814 3.027873 3.06535)
198772.3    (3.36e-01): par = (16191.06 184.036 323.7503 72.44112 1.13643 1.331797 1.168736 3.036238 3.070983)
197021.8    (3.21e-01): par = (148960.4 183.8998 324.6251 592.3545 1.136896 1.33284 1.133819 3.052741 3.0821)
      192787. (2.84e-01): par = (12802762 183.7682 325.4709 45115.8 1.137346 1.333833 1.097287 3.068791 3.092921)
Error in nls(formula, data = data, start = start, algorithm = algorithm,  : 
  singular gradient
> 
> ## Compare coeffs:
> rbind(c.true = unlist(m1.st),
+       cl0 = coef(m.c00),
+       cl = coef(m.cl), rob = coef(mrob),
+       c2 = coef(m.c2))#, r.2 = coef(mr.2))
                Wm1      Wm2      Wm3           a1        a2       a3        b1
c.true 2.198000e+02 265.9000 343.4000 1.461000e+00 1.4930000 1.294000 2.8890000
cl0    5.795709e+02 -65.2797 343.0101 3.036982e+00 0.1953332 1.132643 0.1499419
cl     4.899173e+02 615.5279 380.0640 2.342740e+00 2.1896019 1.371278 2.3973324
rob    2.848698e+02 263.5836 343.0199 1.678283e+00 1.4824746 1.292989 2.7342154
c2     3.194288e+08 152.2659 362.7797 2.847631e+06 1.0777562 1.334812 1.0011760
             b2       b3
c.true 2.838000 4.046000
cl0    3.669756 3.655383
cl     2.594862 3.594968
rob    2.858920 4.047651
c2     3.541478 3.766120
> ## Compare  fit
> 
> ## Now for plotting --- nice would be xyplot, but I don't easily see how:
> 
> 
> (yl2  <- range(biomassTill[,"Biom.2"]))
[1]   0.9085065 513.6421369
> (ylim <- range(biomassTill[,"Biomass"]))# --> *not* showing the two outliers!
[1]   0.5412327 579.6046045
> ## or even a bit more robustly:
> ## sfsmisc::rrange(biomassTill[,"Biom.2"]) ##-> -201.3064  394.0914
> 
> ## using global data + fits from above
> p.biomass.fits <- function(ylim = c(-200, 400), n = 257, f.DVS = 0.1,
+                            leg.txt =
+                                c(outer(c("nls()   ", "nlrob()"),
+                                        c("", "[ + 2 outl.]"), paste)),
+                            col = c("blue2","blue3","tomato","red3"),
+                            lty = c(2,1,2,1),
+                            lwd = 2)
+ {
+     ## more and equispaced DVS values for nice plot:
+     rr <- extendrange(biomassTill[,"DVS"], f=f.DVS)
+     bbDVS <- seq(rr[1], rr[2], length = n)
+     b.Till <- biomassTill[,"Tillage"]
+     nP <- nlevels(b.Till) # == 3
+     m <- length(leg.txt)
+     col <- rep_len(col, m)
+     lwd <- rep_len(lwd, m)
+     lty <- rep_len(lty, m)
+     ## Prefer xyplot() - this is ugly but works (and tests predict(*, <subset>)):
+     op <- par(mfrow = c(nP,1), mar = .1 + c(3, 3, 2, 1), mgp = c(1.25, 0.6, 0))
+     on.exit(par(op))
+     for(lev in levels(b.Till)) {
+         cat(lev,":\n--------\n")
+         dsub <- subset(biomassTill, Tillage == lev)
+         plot(Biom.2 ~ DVS, data = dsub, ylim=ylim, main = paste("Tillage = ", lev))
+         grid()
+         dd <- data.frame(Tillage = factor(rep.int(lev, n), levels=levels(b.Till)),
+                          DVS = bbDVS)
+         lines(predict(m.cl, dd) ~ DVS, data=dd, col=col[1], lty=lty[1], lwd=lwd[1])
+         lines(predict(mrob, dd) ~ DVS, data=dd, col=col[2], lty=lty[2], lwd=lwd[2])
+         lines(predict(m.c2, dd) ~ DVS, data=dd, col=col[3], lty=lty[3], lwd=lwd[3])
+         ## lines(predict(mr.2, dd) ~ DVS, data=dd, col=col[4], lty=lty[4], lwd=lwd[4])
+         if(lev == "CA-")
+             legend("top", leg.txt, col = col, lty=lty, lwd=lwd,
+                    inset=.02, bg = "gray96") #, bty="n")
+     }
+ }
> 
> ## showing all data points:
> p.biomass.fits(ylim = yl2)
CA- :
--------
CA+ :
--------
CT :
--------
> ## more interesting:
> p.biomass.fits()
CA- :
--------
CA+ :
--------
CT :
--------
> 
> 
> cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons''
Time elapsed:  1.25 0.14 1.39 NA NA 
> 
> proc.time()
   user  system elapsed 
   1.25    0.14    1.39