R Under development (unstable) (2024-07-10 r86888 ucrt) -- "Unsuffered Consequences"
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> library(fitdistrplus)
Loading required package: MASS
Loading required package: survival
> 
> 
> 
> 
> # (1) fit a user-defined continuous distribution (Gumbel) to censored data.
> #
> 
> data(fluazinam)
> log10EC50 <-log10(fluazinam)
> # definition of the Gumbel distribution
> dgumbel  <-  function(x,a,b) 1/b*exp((a-x)/b)*exp(-exp((a-x)/b))
> pgumbel  <-  function(q,a,b) exp(-exp((a-q)/b))
> qgumbel  <-  function(p,a,b) a-b*log(-log(p))
> 
> mledist(log10EC50, "gumbel", start=list(a=0,b=2), optim.method="Nelder-Mead")
$estimate
       a        b 
1.632726 1.144113 

$convergence
[1] 0

$value
[1] 20.27771

$hessian
          a         b
a 10.683955 -4.764691
b -4.764691 16.810611

$optim.function
[1] "optim"

$optim.method
[1] "Nelder-Mead"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      65       NA 

$optim.message
NULL

$loglik
[1] -20.27771

$vcov
NULL

> mledist(log10EC50, "gumbel", start=list(a=0,b=2)) #default NM
$estimate
       a        b 
1.632726 1.144113 

$convergence
[1] 0

$value
[1] 20.27771

$hessian
          a         b
a 10.683955 -4.764691
b -4.764691 16.810611

$optim.function
[1] "optim"

$optim.method
[1] "Nelder-Mead"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      65       NA 

$optim.message
NULL

$loglik
[1] -20.27771

$vcov
NULL

> 
> 
> try(mledist(rbind(log10EC50, c("a", "b")), "gamma"))
Error in checkCensoredDataFrameNAInfNan(censdata) : 
  censdata contain NaN (not a numeric) values.
> try(mledist(rbind(log10EC50, c(NA, NA)), "gamma"))
Error in checkCensoredDataFrameNAInfNan(censdata) : 
  censdata contain two NA values on the same line.
> try(mledist(rbind(log10EC50, c(3, Inf)), "gamma"))
Error in checkCensoredDataFrameNAInfNan(censdata) : 
  censdata contain Inf (infinite) values.
> try(mledist(rbind(log10EC50, c(3, NaN)), "gamma"))
Error in checkCensoredDataFrameNAInfNan(censdata) : 
  censdata contain NaN (not a numeric) values.
> 
> 
> 
> 
> 
> # (2) test optimization arguments to censored data MLE.
> #
> 
> mledist(log10EC50, "lnorm", optim.method="BFGS")
$estimate
  meanlog     sdlog 
0.6229737 0.9281694 

$convergence
[1] 0

$value
[1] 21.06638

$hessian
          meanlog     sdlog
meanlog 15.358336 -2.676329
sdlog   -2.676329 23.992338

$optim.function
[1] "optim"

$optim.method
[1] "BFGS"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      13        6 

$optim.message
NULL

$loglik
[1] -21.06638

$vcov
NULL

> mledist(log10EC50, "lnorm", optim.method="Nelder")
$estimate
  meanlog     sdlog 
0.6230097 0.9282263 

$convergence
[1] 0

$value
[1] 21.06638

$hessian
          meanlog     sdlog
meanlog 15.356415 -2.676889
sdlog   -2.676889 23.985490

$optim.function
[1] "optim"

$optim.method
[1] "Nelder-Mead"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      45       NA 

$optim.message
NULL

$loglik
[1] -21.06638

$vcov
NULL

> 
> #optim() is used
> mledist(log10EC50, "lnorm", optim.method="L-BFGS-B", lower=0)
$estimate
  meanlog     sdlog 
0.6229875 0.9281720 

$convergence
[1] 0

$value
[1] 21.06638

$hessian
          meanlog     sdlog
meanlog 15.358242 -2.676762
sdlog   -2.676762 23.992168

$optim.function
[1] "optim"

$optim.method
[1] "L-BFGS-B"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
       9        9 

$optim.message
[1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH"

$loglik
[1] -21.06638

$vcov
NULL

> mledist(log10EC50, "lnorm", optim.method="BFGS", lower=0) #a simple warning
$estimate
  meanlog     sdlog 
0.6229875 0.9281720 

$convergence
[1] 0

$value
[1] 21.06638

$hessian
          meanlog     sdlog
meanlog 15.358242 -2.676762
sdlog   -2.676762 23.992168

$optim.function
[1] "optim"

$optim.method
[1] "L-BFGS-B"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
       9        9 

$optim.message
[1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH"

$loglik
[1] -21.06638

$vcov
NULL

Warning message:
In mledist(log10EC50, "lnorm", optim.method = "BFGS", lower = 0) :
  The BFGS method cannot be used with bounds without provided the gradient. The method is changed to L-BFGS-B.
> 
> #constrOptim() is used
> mledist(log10EC50, "lnorm", optim.method="Nelder", lower=0)
$estimate
  meanlog     sdlog 
0.6230097 0.9282263 

$convergence
[1] 0

$value
[1] 21.06638

$hessian
NULL

$optim.function
[1] "constrOptim"

$optim.method
[1] "Nelder-Mead"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      45       NA 

$optim.message
NULL

$loglik
[1] -21.06638

$vcov
NULL

> mledist(log10EC50, "lnorm", lower=0) #error
$estimate
  meanlog     sdlog 
0.6230097 0.9282263 

$convergence
[1] 0

$value
[1] 21.06638

$hessian
NULL

$optim.function
[1] "constrOptim"

$optim.method
[1] "Nelder-Mead"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      45       NA 

$optim.message
NULL

$loglik
[1] -21.06638

$vcov
NULL

> 
> # (3) weighted MLE
> #
> xleft <- c(-1.8, -0.6, -0.1, 0.07, 0.14, 1, 1.2, 1.2, 1.2)
> xright <- c(-1.8, -0.6, -0.1, 0.07, 0.14, 1, NA, NA, NA)
> d <- data.frame(left = xleft, right = xright)
> f1 <- mledist(d, "norm")
> 
> dbis <- data.frame(left = c(-1.8, -0.6, -0.1, 0.07, 0.14, 1, 1.2), 
+                    right = c(-1.8, -0.6, -0.1, 0.07, 0.14, 1, NA))
> f2 <- mledist(dbis, "norm", weights = c(rep(1,6),3))
Warning message:
In mledist(dbis, "norm", weights = c(rep(1, 6), 3)) :
  weights are not taken into account in the default initial values
> 
> # f1 and f2 must give quite the same results (only starting values differ)
> f1$estimate
     mean        sd 
0.5447786 1.3422448 
> f2$estimate
     mean        sd 
0.5448978 1.3423076 
> 
> # (4) test the definition of fix.arg/start.arg as functions
> #     if defined as functions, start.arg and fix.arg must be
> #     functions of pseudo data (output pseudo of cens2pseudo())
> 
> mledist(d, "norm", start = function(x) list(mean = 0, sd = 1))$estimate
     mean        sd 
0.5448718 1.3420260 
> mledist(d, "norm", start = function(x) list(mean = mean(x), sd = 1))$estimate
     mean        sd 
0.5447851 1.3422520 
> mledist(d, "norm", fix.arg = function(x) list(mean = 0))$estimate
      sd 
1.399337 
> mledist(d, "norm", fix.arg = function(x) list(mean = 0.544))$estimate
      sd 
1.341995 
> mledist(d, "norm", fix.arg = function(x) list(mean = mean(x)))$estimate
      sd 
1.327269 
> 
> 
> proc.time()
   user  system elapsed 
   1.59    0.39    1.92