Running examples in ‘fitdistrplus-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: CIcdfplot
> ### Title: Empirical cumulative distribution function with pointwise
> ###   confidence intervals on probabilities or on quantiles
> ### Aliases: CIcdfplot
> ### Keywords: distribution
> 
> ### ** Examples
> 
> # We choose a low number of bootstrap replicates in order to satisfy CRAN running times
> # constraint.
> # For practical applications, we recommend to use at least niter=501 or niter=1001.
> 
> if (requireNamespace ("ggplot2", quietly = TRUE)) {ggplotEx <- TRUE}
> 
> # (1) Fit of an exponential distribution
> #
> 
> set.seed(123)
> s1 <- rexp(50, 1)
> f1 <- fitdist(s1, "exp")
> b1 <- bootdist(f1, niter= 11) #voluntarily low to decrease computation time
> 
> # plot 95 percent bilateral confidence intervals on y values (probabilities)
> CIcdfplot(b1, CI.level= 95/100, CI.output = "probability")
> if (ggplotEx) CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", plotstyle = "ggplot")
> 
> # plot of the previous intervals as a band 
> CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", 
+   CI.fill = "pink", CI.col = "red")
> if (ggplotEx) CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", 
+   CI.fill = "pink", CI.col = "red", plotstyle = "ggplot")
> 
> # plot of the previous intervals as a band without empirical and fitted dist. functions
> CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", CI.only = TRUE,
+   CI.fill = "pink", CI.col = "red")
> if (ggplotEx) CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", CI.only = TRUE,
+   CI.fill = "pink", CI.col = "red", plotstyle = "ggplot")
>   
> # same plot without contours
> CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", CI.only = TRUE,
+   CI.fill = "pink", CI.col = "pink")
> if (ggplotEx) CIcdfplot(b1, CI.level= 95/100, CI.output = "probability", CI.only = TRUE,
+   CI.fill = "pink", CI.col = "pink", plotstyle = "ggplot")
> 
> # plot 95 percent bilateral confidence intervals on x values (quantiles)
> CIcdfplot(b1, CI.level= 95/100, CI.output = "quantile")
> if (ggplotEx) CIcdfplot(b1, CI.level= 95/100, CI.output = "quantile", plotstyle = "ggplot")
> 
> 
> # plot 95 percent unilateral confidence intervals on quantiles
> CIcdfplot(b1, CI.level = 95/100, CI.output = "quant", CI.type = "less", 
+   CI.fill = "grey80", CI.col = "black", CI.lty = 1)
> if (ggplotEx) CIcdfplot(b1, CI.level = 95/100, CI.output = "quant", CI.type = "less", 
+   CI.fill = "grey80", CI.col = "black", CI.lty = 1, plotstyle = "ggplot")
>     
> CIcdfplot(b1, CI.level= 95/100, CI.output = "quant", CI.type = "greater",
+   CI.fill = "grey80", CI.col = "black", CI.lty = 1)
> if (ggplotEx) CIcdfplot(b1, CI.level= 95/100, CI.output = "quant", CI.type = "greater",
+   CI.fill = "grey80", CI.col = "black", CI.lty = 1, plotstyle = "ggplot")
> 
> # (2) Fit of a normal distribution on acute toxicity log-transformed values of 
> # endosulfan for nonarthropod invertebrates, using maximum likelihood estimation
> # to estimate what is called a species sensitivity distribution 
> # (SSD) in ecotoxicology, followed by estimation of the 5, 10 and 20 percent quantile  
> # values of the fitted distribution, which are called the 5, 10, 20 percent hazardous 
> # concentrations (HC5, HC10, HC20) in ecotoxicology, with their
> # confidence intervals, from a small number of bootstrap 
> # iterations to satisfy CRAN running times constraint and plot of the band
> # representing pointwise confidence intervals on any quantiles (any HCx values)
> # For practical applications, we recommend to use at least niter=501 or niter=1001.
> #
> 
> data(endosulfan)
> log10ATV <- log10(subset(endosulfan, group == "NonArthroInvert")$ATV)
> namesATV <- subset(endosulfan, group == "NonArthroInvert")$taxa
> fln <- fitdist(log10ATV, "norm")
> bln <- bootdist(fln, bootmethod ="param", niter=101)
> quantile(bln, probs = c(0.05, 0.1, 0.2))
(original) estimated quantiles for each specified probability (non-censored data)
           p=0.05    p=0.1  p=0.2
estimate 1.744227 2.080093 2.4868
Median of bootstrap estimates
           p=0.05    p=0.1    p=0.2
estimate 1.844443 2.190122 2.565053

two-sided 95 % CI of each quantile
         p=0.05    p=0.1    p=0.2
2.5 %  1.334340 1.697255 2.099378
97.5 % 2.531564 2.770455 3.053706
> CIcdfplot(bln, CI.output = "quantile", CI.fill = "lightblue", CI.col = "blue",
+           xlim = c(0,5), name.points=namesATV)
> if (ggplotEx) CIcdfplot(bln, CI.output = "quantile", CI.fill = "lightblue", CI.col = "blue",
+   xlim = c(0,5), name.points=namesATV, plotstyle = "ggplot")
> 
> 
> # (3) Same type of example as example (2) from ecotoxicology
> # with censored data
> #
> data(salinity)
> log10LC50 <-log10(salinity)
> fln <- fitdistcens(log10LC50,"norm")
Error in mledist(censdata, distname, start = arg_startfix$start.arg, fix.arg = arg_startfix$fix.arg,  : 
  data must be a numeric vector of length greater than 1 for non censored data or a dataframe with two columns named left and right and more than one line for censored data
Calls: fitdistcens -> mledist
Execution halted