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) non-censored data (continuous)
> #
> 
> s1 <- NULL
> s2 <- list("mean"=2)
> s0 <- list("mean"=2, "sd"=1)
> s3 <- function(x)
+   list("mean"=1.01*mean(x)) 
> s4 <- function(x)
+   list("mean"=1.01*mean(x), "sd"=sd(x)) 
> 
> f1 <- NULL  
> f2 <- list("sd"=3)
> f3 <- function(x) 
+   list("sd"=1.01*sd(x))  
> 
> x <- rnorm(1000)
> 
> #redefine normal distribution for better check
> dnorm2 <- dnorm
> pnorm2 <- pnorm
> qnorm2 <- qnorm
> rnorm2 <- rnorm
> mnorm2 <- function(order, mean, sd)
+   ifelse(order == 1, mean, sd^2)
> memp  <-  function(x, order) mean(x^order)
> 
> # both NULL
> mf1 <- mledist(x, "norm", start=s1, fix.arg=f1)
> mf1 <- mmedist(x, "norm", start=s1, fix.arg=f1)
> mf1 <- qmedist(x, "norm", start=s1, fix.arg=f1, probs=1:2/3)
> mf1 <- mgedist(x, "norm", start=s1, fix.arg=f1)
> 
> fit1 <- fitdist(x, "norm", start=s1, fix.arg=f1)
> boot1 <- bootdist(fit1, niter=10)
> 
> # both named list
> mf1 <- mledist(x, "norm2", start=s2, fix.arg=f2)
> mf1 <- mmedist(x, "norm2", start=s2, fix.arg=f2, order=1, memp=memp)
> mf1 <- qmedist(x, "norm2", start=s2, fix.arg=f2, probs=1/3)
> mf1 <- mgedist(x, "norm2", start=s2, fix.arg=f2)
> 
> fit1 <- fitdist(x, "norm2", start=s2, fix.arg=f2)
> boot1 <- bootdist(fit1, niter=10)
> 
> # named list and NULL
> mf1 <- mledist(x, "norm2", start=s0, fix.arg=f1)
> mf1 <- mmedist(x, "norm2", start=s0, fix.arg=f1, order=1:2, memp=memp)
> mf1 <- qmedist(x, "norm2", start=s0, fix.arg=f1, probs=1:2/3)
> mf1 <- mgedist(x, "norm2", start=s0, fix.arg=f1)
> 
> fit1 <- fitdist(x, "norm2", start=s0, fix.arg=f1)
> boot1 <- bootdist(fit1, niter=10)
> 
> # NULL and named list 
> mf1 <- mledist(x, "norm", start=s1, fix.arg=f2)
> mf1 <- qmedist(x, "norm", start=s1, fix.arg=f2, probs=1/3)
> mf1 <- mgedist(x, "norm", start=s1, fix.arg=f2)
> 
> fit1 <- fitdist(x, "norm", start=s1, fix.arg=f2)
> boot1 <- bootdist(fit1, niter=10)
> 
> # both function
> mf1 <- mledist(x, "norm2", start=s3, fix.arg=f3)
> mf1 <- mmedist(x, "norm2", start=s3, fix.arg=f3, order=1, memp=memp)
> mf1 <- qmedist(x, "norm2", start=s3, fix.arg=f3, probs=1/3)
> mf1 <- mgedist(x, "norm2", start=s3, fix.arg=f3)
> 
> fit1 <- fitdist(x, "norm2", start=s3, fix.arg=f3)
> boot1 <- bootdist(fit1, niter=10)
> 
> # function and NULL
> mf1 <- mledist(x, "norm2", start=s4, fix.arg=f1)
> mf1 <- mmedist(x, "norm2", start=s4, fix.arg=f1, order=1:2, memp=memp)
> mf1 <- qmedist(x, "norm2", start=s4, fix.arg=f1, probs=1:2/3)
> mf1 <- mgedist(x, "norm2", start=s4, fix.arg=f1)
> 
> fit1 <- fitdist(x, "norm2", start=s4, fix.arg=f1)
> boot1 <- bootdist(fit1, niter=10)
> 
> # NULL and function
> mf1 <- mledist(x, "norm", start=s1, fix.arg=f3)
> mf1 <- qmedist(x, "norm", start=s1, fix.arg=f3, probs=1/3)
> mf1 <- mgedist(x, "norm", start=s1, fix.arg=f3)
> 
> fit1 <- fitdist(x, "norm", start=s1, fix.arg=f3)
> boot1 <- bootdist(fit1, niter=10)
> 
> # should raise error for too less parameters
> try(mgedist(x, "norm", start=s2, fix.arg=f1))
$estimate
       mean 
-0.03735531 

$convergence
[1] 0

$value
[1] 0.02598352

$hessian
       mean
mean 184.85

$optim.function
[1] "optim"

$optim.method
[1] "BFGS"

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      18        7 

$optim.message
NULL

$loglik
[1] -1417.566

$gof
[1] "CvM"

Warning message:
In checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  :
  Some parameter names have no starting/fixed value but have a default value: sd.
> try(fitdist(x, "norm", start=s2, fix.arg=f1))
Fitting of the distribution ' norm ' by maximum likelihood 
Parameters:
       estimate Std. Error
mean -0.0310707 0.03162278
> # should raise error for too much parameters
> try(mgedist(x, "norm", start=s0, fix.arg=f2))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  A distribution parameter cannot be specified both in 'start' and 'fix.arg'.
> try(fitdist(x, "norm", start=s0, fix.arg=f2))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  A distribution parameter cannot be specified both in 'start' and 'fix.arg'.
> # should raise error for NA value
> try(mgedist(x, "norm", start=s1, fix.arg=list(sd=NA)))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  'fix.arg' should not have NA or NaN values.
> try(fitdist(x, "norm", start=list(sd=NA)))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  'start' should not have NA or NaN values.
> # should raise error for inconsistent parameter
> try(mgedist(x, "norm", start=function(x) list("toto"=1)))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  'start' must specify names which are arguments to 'distr'.
> try(fitdist(x, "norm", fix=list(toto=2)))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  'fix.arg' must specify names which are arguments to 'distr'.
> 
> #test unset arguments
> dbeta2<-function(x, shape1, ncp2) 
+   dbeta(x, shape1, shape1, ncp2)
> x <- rbeta(1e2, 3, 3)
> try(fitdist(x, "beta2", start=list(shape1=2)))
Error in checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg,  : 
  Some parameter names have no starting/fixed value: ncp2.
> 
> dbeta3<-function(x, shape1, ncp2=0) 
+   dbeta(x, shape1, shape1, ncp2)
> fitdist(x, "beta3", start=list(shape1=2))
Fitting of the distribution ' beta3 ' by maximum likelihood 
Parameters:
       estimate Std. Error
shape1 3.293974  0.4346781
Warning message:
In fitdist(x, "beta3", start = list(shape1 = 2)) :
  The pbeta3 function must be defined
> 
> 
> 
> # (2) censored data
> #
> 
> data(salinity)
> log10LC50 <-log10(salinity)
> 
> s1 <- NULL
> s2 <- list("mean"=2)
> s0 <- list("mean"=2, "sd"=1)
> s3 <- function(x) list("mean"=mean(x))
> 
> f1 <- NULL  
> f2 <- list("sd"=3)
> f3 <- function(x) list("sd"=sd(x))
> 
> fitdistcens(log10LC50, "norm", start=s1, fix.arg = f1)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
      estimate
mean 1.4702582
sd   0.2154709
> fitdistcens(log10LC50, "norm", start=s1, fix.arg = f2)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
     estimate
mean 2.966347
Fixed parameters:
   value
sd     3
> fitdistcens(log10LC50, "norm", start=s2, fix.arg = f2)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
     estimate
mean 2.966826
Fixed parameters:
   value
sd     3
> fitdistcens(log10LC50, "norm", start=s0, fix.arg = f1)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
      estimate
mean 1.4702237
sd   0.2154322
> fitdistcens(log10LC50, "norm", start=s3, fix.arg = f2)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
     estimate
mean 2.966347
Fixed parameters:
   value
sd     3
> fitdistcens(log10LC50, "norm", start=s3, fix.arg = f3)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
     estimate
mean 1.628163
Fixed parameters (computed by a user-supplied function):
       value
sd 0.5788206
> fitdistcens(log10LC50, "norm", start=s1, fix.arg = f3)
Fitting of the distribution ' norm ' on censored data by maximum likelihood 
Parameters:
     estimate
mean 1.628163
Fixed parameters (computed by a user-supplied function):
       value
sd 0.5788206
> 
> 
> fit1 <- fitdistcens(log10LC50, "norm", start=s1, fix.arg = f1)
> boot1 <- bootdistcens(fit1, niter = 10)
> 
> fit1 <- fitdistcens(log10LC50, "norm", start=s3, fix.arg = f2)
> boot1 <- bootdistcens(fit1, niter = 10)
> 
> fit1 <- fitdistcens(log10LC50, "norm", start=s2, fix.arg = f3)
> boot1 <- bootdistcens(fit1, niter = 10)
> 
> # (3) non-censored data (discrete)
> #
> 
> n <- 200
> trueval <- c("size"=10, "prob"=3/4, "mu"=10/3)
> x <- rnbinom(n, trueval["size"], trueval["prob"])
> 
> mledist(x, "nbinom")
$estimate
    size       mu 
8.941108 3.554799 

$convergence
[1] 0

$value
[1] 431.4228

$hessian
              size            mu
size  0.0953703676 -0.0002569536
mu   -0.0002569536 40.2596502767

$optim.function
[1] "optim"

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

$fix.arg
NULL

$fix.arg.fun
NULL

$weights
NULL

$counts
function gradient 
      37       NA 

$optim.message
NULL

$loglik
[1] -431.4228

$vcov
NULL

> fitdist(x, "nbinom")
Fitting of the distribution ' nbinom ' by maximum likelihood 
Parameters:
     estimate Std. Error
size 8.941108  3.2381225
mu   3.554799  0.1576032
> 
> 
> # (4) non-censored data (continuous) external distributions
> #
> 
> data("endosulfan")
> ATV <-endosulfan$ATV
> fendo.ln <- fitdist(ATV, "lnorm")
> fendo.g <- fitdist(ATV, "gamma", start=list(shape=2, scale=1), lower=0)
> require("actuar")
Loading required package: actuar

Attaching package: 'actuar'

The following objects are masked from 'package:stats':

    sd, var

The following object is masked from 'package:grDevices':

    cm

> fendo.ll <- fitdist(ATV, "llogis", start = list(shape = 1, scale = 500))
> fendo.P <- fitdist(ATV, "pareto", start = list(shape = 1, scale = 500))
> fendo.B <- fitdist(ATV, "burr", start = list(shape1 = 0.3, shape2 = 1, 
+                                              rate = 1))
> 
> proc.time()
   user  system elapsed 
   2.96    0.20    3.15