R Under development (unstable) (2026-01-19 r89308 ucrt) -- "Unsuffered Consequences"
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> library(mbbefd)
Loading required package: fitdistrplus
Loading required package: MASS
Loading required package: survival
Loading required package: alabama
Loading required package: numDeriv
Loading required package: Rcpp
Package:  mbbefd
Version:  0.8.14
Date:     
BugReport: https://github.com/spedygiorgio/mbbefd/issues


> library(fitdistrplus)
> 
> n <- 1e3
> nboot <- 1000
> nboot <- 10
> set.seed(123456)
> lossrate <- rmbbefd(n, 1/2, 1/10)
> 
> 
> f1 <- fitDR(lossrate, "mbbefd")
> summary(f1)
Fitting of the distribution ' mbbefd ' by maximum likelihood 
Parameters : 
   estimate Std. Error
a 0.5553806 0.11997101
b 0.1070020 0.01648866
Loglikelihood:  -553.0793   AIC:  1110.159   BIC:  1119.974 
Correlation matrix:
          a         b
a 1.0000000 0.9174775
b 0.9174775 1.0000000

> 
> #should be similar
> f0 <- fitdist(lossrate, "mbbefd", start= list(a=1/4, b=1/4))
Warning message:
In fitdist(lossrate, "mbbefd", start = list(a = 1/4, b = 1/4)) :
  The dmbbefd function should return a vector of with NaN values when input has inconsistent values and not raise an error
> summary(f0)
Fitting of the distribution ' mbbefd ' by maximum likelihood 
Parameters : 
   estimate Std. Error
a 0.5545699 0.11957317
b 0.1068949 0.01645331
Loglikelihood:  -553.0793   AIC:  1110.159   BIC:  1119.974 
Correlation matrix:
          a         b
a 1.0000000 0.9172606
b 0.9172606 1.0000000

> 
> 
> cdfcomp(f1, do.points=FALSE)
> qqcomp(f1)
> vcov(f1)
            a           b
a 0.014393043 0.001814919
b 0.001814919 0.000271876
> 
> 
> # llsurface(plot.min=c(0, 0), plot.max=c(2, 1/2), plot.arg=c("a", "b"), obs=lossrate, distr="mbbefd", nlevels=25)
> # points(f1$estimate["a"], f1$estimate["b"], pch="+", col="red")
> # points(1/2, 1/10, pch="x", col="black")
> 
> b1 <- bootDR(f1, niter=nboot, silent=TRUE)
> plot(b1, enhance=TRUE, trueval=c(1/2, 1/10))
> 
> 
> f2 <- fitDR(lossrate, "mbbefd", method="tlmme")
> summary(f2)
Parameters : 
  estimate
1       NA
Loglikelihood:  NA   AIC:  NA   BIC:  NA 
> 
> 
> 
> set.seed(123456)
> lossrate <- rmbbefd(n, -1/2, 5)
> 
> 
> f1 <- fitDR(lossrate, "mbbefd")
> summary(f1)
Fitting of the distribution ' mbbefd ' by maximum likelihood 
Parameters : 
    estimate Std. Error
a -0.4973342 0.02217064
b  5.3524451 1.05189781
Loglikelihood:  -549.6747   AIC:  1103.349   BIC:  1113.165 
Correlation matrix:
          a         b
a 1.0000000 0.7336745
b 0.7336745 1.0000000

> 
> b1 <- bootDR(f1, niter=nboot, silent=TRUE)
> plot(b1, enhance=TRUE, trueval=c(-1/2, 5))
> 
> 
> proc.time()
   user  system elapsed 
  20.15    5.07   25.21