Last updated on 2024-05-10 15:52:30 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.1-11 | 16.95 | 468.75 | 485.70 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.1-11 | 12.47 | 340.10 | 352.57 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.1-11 | 611.27 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.1-11 | 783.91 | OK | |||
| r-devel-windows-x86_64 | 1.1-11 | 15.00 | 354.00 | 369.00 | OK | |
| r-patched-linux-x86_64 | 1.1-11 | 20.54 | 451.89 | 472.43 | OK | |
| r-release-linux-x86_64 | 1.1-11 | 15.78 | 440.65 | 456.43 | OK | |
| r-release-macos-arm64 | 1.1-11 | 185.00 | OK | |||
| r-release-windows-x86_64 | 1.1-11 | 16.00 | 346.00 | 362.00 | ERROR | |
| r-oldrel-macos-arm64 | 1.1-11 | 188.00 | OK | |||
| r-oldrel-macos-x86_64 | 1.1-11 | 529.00 | OK | |||
| r-oldrel-windows-x86_64 | 1.1-11 | 22.00 | 429.00 | 451.00 | OK |
Version: 1.1-11
Check: tests
Result: ERROR
Running 't-CIcdfplot.R' [14s]
Running 't-Surv2fitdistcens.R' [2s]
Running 't-bootdist.R' [5s]
Running 't-bootdistcens.R' [2s]
Running 't-cdfcomp.R' [3s]
Running 't-cdfcompcens.R' [4s]
Running 't-cvg-algo.R' [0s]
Running 't-denscomp.R' [4s]
Running 't-descdist.R' [2s]
Running 't-detectbound.R' [2s]
Running 't-fitbench.R' [0s]
Running 't-fitdist-customoptim.R' [2s]
Running 't-fitdist.R' [3s]
Running 't-fitdistcens.R' [4s]
Running 't-gen-max-spacing-estim.R' [2s]
Running 't-getparam.R' [1s]
Running 't-gofstat.R' [2s]
Running 't-init-actuar.R' [0s]
Running 't-llplot.R' [3s]
Running 't-lnL-surf.R' [2s]
Running 't-logLik-vcov-coef.R' [2s]
Running 't-manageparam.R' [2s]
Running 't-mgedist.R' [3s]
Running 't-mledist-cens.R' [2s]
Running 't-mledist-nocens.R' [3s]
Running 't-mledist-paramsupport.R' [3s]
Running 't-mmedist.R' [4s]
Running 't-msedist.R' [3s]
Running 't-parallel.R' [0s]
Running 't-plotdist.R' [2s]
Running 't-plotdistcens.R' [2s]
Running 't-ppcomp.R' [3s]
Running 't-ppcompcens.R' [3s]
Running 't-prefit.R' [2s]
Running 't-qme-discrete.R' [7s]
Running 't-qmedist.R' [5s]
Running 't-qqcomp.R' [4s]
Running 't-qqcompcens.R' [4s]
Running 't-quantiledist.R' [2s]
Running 't-startfixarg-overall.R' [3s]
Running 't-startingvalues.R' [2s]
Running 't-util-npmle.R' [2s]
Running 't-util-npsurv-mainfunction.R' [1s]
Running 't-util-testdensity.R' [2s]
Running 't-weird-ppcomp-cens.R' [2s]
Running 't-weird-qqcomp-cens.R' [2s]
Running the tests in 'tests/t-CIcdfplot.R' failed.
Complete output:
> library(fitdistrplus)
Loading required package: MASS
Loading required package: survival
>
> nbboot <- 201
> nbboot <- 10
> ggplotEx <- requireNamespace("ggplot2", quietly = TRUE)
>
> # (1) Fit of a gamma distribution
> #
>
> set.seed(123)
> s1 <- rgamma(20, 3, 2)
> f1 <- fitdist(s1, "gamma")
> b1 <- bootdist(f1, niter=nbboot, silent=TRUE)
>
> plot(b1)
> quantile(b1)
(original) estimated quantiles for each specified probability (non-censored data)
p=0.1 p=0.2 p=0.3 p=0.4 p=0.5 p=0.6 p=0.7
estimate 0.4742226 0.672897 0.8486169 1.022154 1.20499 1.408707 1.650739
p=0.8 p=0.9
estimate 1.966843 2.466269
Median of bootstrap estimates
p=0.1 p=0.2 p=0.3 p=0.4 p=0.5 p=0.6 p=0.7
estimate 0.5083059 0.6866909 0.8522568 1.018742 1.200786 1.384358 1.577513
p=0.8 p=0.9
estimate 1.797666 2.213844
two-sided 95 % CI of each quantile
p=0.1 p=0.2 p=0.3 p=0.4 p=0.5 p=0.6 p=0.7
2.5 % 0.3930866 0.5545204 0.6866101 0.8156534 0.9504778 1.099636 1.275705
97.5 % 0.7636623 0.9342928 1.0731198 1.2027355 1.3333688 1.479356 1.762055
p=0.8 p=0.9
2.5 % 1.498104 1.827576
97.5 % 2.151721 2.778154
>
> par(mfrow=c(1,2))
> CIcdfplot(b1, CI.level=95/100, CI.output = "probability", CI.fill="grey80", CI.col="black")
> CIcdfplot(b1, CI.level=95/100, CI.output = "quantile", datacol="blue")
> if(ggplotEx) CIcdfplot(b1, CI.level=95/100, CI.output = "probability", CI.fill="grey80", CI.col="black", plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=95/100, CI.output = "quantile", datacol="blue", plotstyle = "ggplot")
>
> par(mfrow=c(1,2))
> CIcdfplot(b1, CI.level=85/100, CI.output = "probability")
> CIcdfplot(b1, CI.level=85/100, CI.output = "quantile")
> if(ggplotEx) CIcdfplot(b1, CI.level=85/100, CI.output = "probability", plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=85/100, CI.output = "quantile", plotstyle = "ggplot")
>
> par(mfrow=c(1,2))
> CIcdfplot(b1, CI.level=90/100, CI.output = "probability")
> CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="black", CI.type = "less",
+ CI.fill="grey85", verticals=TRUE, datacol="blue", do.points=FALSE)
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "probability", plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="black", CI.type = "less",
+ CI.fill="grey85", verticals=TRUE, datacol="blue", do.points=FALSE, plotstyle = "ggplot")
>
> par(mfrow=c(1,2))
> CIcdfplot(b1, CI.level=90/100, CI.output = "probability", CI.type = "greater")
> CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="black", CI.type = "greater",
+ CI.fill="grey90", datacol="blue", datapch=21)
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "probability", CI.type = "greater", plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="black", CI.type = "greater",
+ CI.fill="grey90", datacol="blue", datapch=21, plotstyle = "ggplot")
>
> par(mfrow=c(1,1))
> CIcdfplot(b1, CI.level=90/100, CI.output = "probability", CI.col="black", CI.type = "less", CI.fill="grey90")
> CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="black", CI.type = "less", CI.fill="grey90",
+ verticals=TRUE, datacol="blue", do.points=FALSE)
> CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="grey90", CI.type = "less", CI.fill="grey90",
+ verticals=TRUE, datacol="blue", do.points=FALSE, CI.only=TRUE)
> CIcdfplot(b1, CI.level=90/100, CI.output = "probability", CI.col="grey85", CI.type = "less", CI.fill="grey90",
+ CI.only = TRUE)
> CIcdfplot(b1, CI.output = "probability", fitlty=3, fitlwd=4)
>
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "probability", CI.col="black", CI.type = "less", CI.fill="grey90", plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="black", CI.type = "less", CI.fill="grey90",
+ verticals=TRUE, datacol="blue", do.points=FALSE, plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "quantile", CI.col="grey90", CI.type = "less", CI.fill="grey90",
+ verticals=TRUE, datacol="blue", do.points=FALSE, CI.only=TRUE, plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.level=90/100, CI.output = "probability", CI.col="grey85", CI.type = "less", CI.fill="grey90",
+ CI.only = TRUE, plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b1, CI.output = "probability", fitlty=3, fitlwd=4, plotstyle = "ggplot")
>
> # (2) an example from ecotoxicology
> # with censored data
> #
> data(salinity)
> log10LC50 <-log10(salinity)
> fln <- fitdistcens(log10LC50,"norm")
> bln <- bootdistcens(fln, niter=nbboot)
> (HC5ln <- quantile(bln,probs = 0.05))
(original) estimated quantiles for each specified probability (censored data)
p=0.05
estimate 1.11584
Median of bootstrap estimates
p=0.05
estimate 1.110188
two-sided 95 % CI of each quantile
p=0.05
2.5 % 1.032713
97.5 % 1.153806
> CIcdfplot(bln, CI.output = "quantile", CI.fill = "lightblue", CI.col = "blue",
+ xlab = "log10(LC50)",xlim=c(0.5,2),lines01 = TRUE)
> if(ggplotEx) CIcdfplot(bln, CI.output = "quantile", CI.fill = "lightblue", CI.col = "blue",
+ xlab = "log10(LC50)",xlim=c(0.5,2),lines01 = TRUE, plotstyle = "ggplot")
>
> # zoom around the HC5 with CI on quantiles
> CIcdfplot(bln, CI.output = "quantile", CI.fill = "lightblue", CI.col = "blue",
+ xlab = "log10(LC50)", lines01 = TRUE, xlim = c(0.8, 1.5), ylim = c(0, 0.1))
> abline(h = 0.05, lty = 1)
> if(ggplotEx) CIcdfplot(bln, CI.output = "quantile", CI.fill = "lightblue", CI.col = "blue",
+ xlab = "log10(LC50)", lines01 = TRUE, xlim = c(0.8, 1.5), ylim = c(0, 0.1), plotstyle = "ggplot") +
+ ggplot2::geom_hline(yintercept = 0.05)
>
> # zoom around the HC5 with CI on probabilities
> CIcdfplot(bln, CI.output = "probability", CI.fill = "lightblue", CI.col = "blue",
+ xlab = "log10(LC50)", lines01 = TRUE, xlim = c(0.8, 1.5), ylim = c(0, 0.1))
> abline(h = 0.05, lty = 1)
> if(ggplotEx) CIcdfplot(bln, CI.output = "probability", CI.fill = "lightblue", CI.col = "blue",
+ xlab = "log10(LC50)", lines01 = TRUE, xlim = c(0.8, 1.5), ylim = c(0, 0.1), plotstyle = "ggplot") +
+ ggplot2::geom_hline(yintercept = 0.05)
>
>
> # (3) An example where the difference between "probability"
> # and "quantile" is clear on the plot
> #
>
> set.seed(123)
> s3 <- rgamma(5, 3, 10)
> f3 <- fitdist(s3, "norm")
> b3 <- bootdist(f3, niter=nbboot, silent=TRUE)
>
> par(mfrow=c(1,2))
> CIcdfplot(b3, CI.level=90/100, CI.output = "probability")
> CIcdfplot(b3, CI.level=90/100, CI.output = "quantile")
>
> if(ggplotEx) CIcdfplot(b3, CI.level=90/100, CI.output = "probability", plotstyle = "ggplot")
> if(ggplotEx) CIcdfplot(b3, CI.level=90/100, CI.output = "quantile", plotstyle = "ggplot")
>
> #some ideas from http://edild.github.io/ssd/
>
> proc.time()
user system elapsed
12.96 0.51 13.46
Flavor: r-release-windows-x86_64