R Under development (unstable) (2023-11-02 r85465 ucrt) -- "Unsuffered Consequences"
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> library(lme4)
Loading required package: Matrix
> 
> allEQ <- function(x,y, tolerance = 4e-4, ...)
+     all.equal.numeric(x,y, tolerance=tolerance, ...)
> 
> (nm1 <- nlmer(circumference ~ SSlogis(age, Asym, xmid, scal) ~ (Asym|Tree),
+               Orange, start = c(Asym = 200, xmid = 725, scal = 350)))
Nonlinear mixed model fit by maximum likelihood  ['nlmerMod']
Formula: circumference ~ SSlogis(age, Asym, xmid, scal) ~ (Asym | Tree)
   Data: Orange
      AIC       BIC    logLik  deviance  df.resid 
 273.1438  280.9205 -131.5719  263.1438        30 
Random effects:
 Groups   Name Std.Dev.
 Tree     Asym 31.646  
 Residual       7.843  
Number of obs: 35, groups:  Tree, 5
Fixed Effects:
 Asym   xmid   scal  
192.1  727.9  348.1  
> fixef(nm1)
    Asym     xmid     scal 
192.0528 727.9045 348.0721 
> 
> if (lme4:::testLevel() > 2) {
+     ## 'Theoph' Data modeling
+     Th.start <- c(lKe = -2.5, lKa = 0.5, lCl = -3)
+ 
+ system.time(nm2 <- nlmer(conc ~ SSfol(Dose, Time,lKe, lKa, lCl) ~
+                          (lKe+lKa+lCl|Subject),
+                          Theoph, start = Th.start,
+                          control=nlmerControl(tolPwrss=1e-8)))
+ print(nm2, corr=FALSE)
+ 
+ system.time(nm3 <- nlmer(conc ~ SSfol(Dose, Time,lKe, lKa, lCl) ~
+                          (lKe|Subject) + (lKa|Subject) + (lCl|Subject),
+                          Theoph, start = Th.start))
+ print(nm3, corr=FALSE)
+ 
+ ## dropping   lKe  from random effects:
+ system.time(nm4 <- nlmer(conc ~ SSfol(Dose, Time,lKe, lKa, lCl) ~ (lKa+lCl|Subject),
+                          Theoph, start = Th.start,
+                          control=nlmerControl(tolPwrss=1e-8)))
+ print(nm4, corr=FALSE)
+ 
+ system.time(nm5 <- nlmer(conc ~ SSfol(Dose, Time,lKe, lKa, lCl) ~
+                          (lKa|Subject) + (lCl|Subject),
+                          Theoph,
+                          start = Th.start,
+                          control=nlmerControl(tolPwrss=1e-8)))
+     print(nm5, corr=FALSE)
+ 
+     ## this has not worked in a *long* time anyway, and PKPDmodels is currently archived, so ...
+     
+     ## if (require("PKPDmodels")) {
+     ##     oral1cptSdlkalVlCl <-
+     ##         PKmod("oral", "sd", list(ka ~ exp(lka), Cl ~ exp(lCl), V ~ exp(lV)))
+     ##     if (FALSE) {
+     ##         ## FIXME: Error in get(nm, envir = nlenv) : object 'k' not found
+     ##         ##  probably with environments/call stack etc.?
+     ##         ## 'pnames' is c("lV","lka","k") -- not ("lV","lka","lCl")
+     ##         ##  nlmer -> nlformula -> MkRespMod
+     ##         ##  pnames are OK in nlformula, but in MkRespMod we try to recover
+     ##         ##   them from the column names of the gradient attribute of the
+     ##         ##   model evaluated in nlenv -- which are wrong.
+     ##         system.time(nm2a <- nlmer(conc ~ oral1cptSdlkalVlCl(Dose, Time, lV, lka, lCl) ~
+     ##                                   (lV+lka+lCl|Subject),
+     ##                                   Theoph, start = c(lV=-1, lka=-0.5, lCl=-3), tolPwrss=1e-8))
+     ##         print(nm2a, corr=FALSE)
+     ##     }
+     ## }
+     
+ }  ## testLevel > 2
> 
> proc.time()
   user  system elapsed 
   2.07    0.28    2.34