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
> 
> 
> 
> #an example with lower bounds for gamma
> 
> data(groundbeef)
> serving <- groundbeef$serving
> #(f1 <-  fitdist(serving, "gamma", optim.method="Nelder-Mead"))
> (f1 <-  fitdist(serving, "gamma", optim.method="Nelder-Mead", lower=0))
Fitting of the distribution ' gamma ' by maximum likelihood 
Parameters:
        estimate Std. Error
shape 4.00748101   0.359909
rate  0.05441516   1.586904
> 
> f1 <- mledist(serving, "gamma", optim.method="Nelder-Mead", lower=0)
> 
> f1 <- fitdist(serving, "gamma", start=as.list(f1$estimate))
> 
> #manual optimization 
> lnl <- function(theta, obs, dfun)
+   sum(do.call(dfun, c(list("x"=obs), theta, "log"=TRUE)))
> 
> H <- optimHess(coef(f1), lnl, obs=serving, dfun=dgamma)
> 
> -solve(H)
            shape         rate
shape 0.116463806 1.580501e-03
rate  0.001580501 2.435556e-05
> vcov(fitdist(serving, "gamma", start=as.list(f1$estimate)))
            shape         rate
shape 0.116463806 1.580501e-03
rate  0.001580501 2.435556e-05
> 
> 
> 
> #an example with lower bounds for ztbinom
> if(FALSE)
+ {
+   library(actuar)
+   n <- 1e3
+   x <- rztbinom(n, 30, 1/2)
+   lnl(c(35, 1/2), obs=x, dfun=dztbinom)
+   
+   optim(c(35, 1/2), lnl, obs=x, dfun=dztbinom, control=list(fnscale=-1))
+   optimHess(c(35, ), lnl, obs=x, dfun=dztbinom)
+   
+   mledist(x, "ztbinom", fix.arg = list(size=30))
+   fitdist(x, "ztbinom", fix.arg = list(size=30))
+   
+   mledist(x, "ztbinom", lower=0)
+   fitdist(x, "ztbinom", lower=0)
+   
+   dztbinom(5, 30.5, 1/2)
+   
+   llsurface(data = x, distr="ztbinom", plot.arg=c("size", "prob"), 
+             min.arg=c(max(x)+1, 0.4), max.arg=c(31, 0.6), back.col = FALSE,
+             main="log-likelihood for ZT binomial distribution")
+   
+ }
> 
> proc.time()
   user  system elapsed 
   1.53    0.31    1.84