Package: topmodels 0.3-0

topmodels: Infrastructure for Forecasting and Assessment of Probabilistic Models

Unified infrastructure for probabilistic models and distributional regressions: Probabilistic forecasting of in-sample and out-of-sample of probabilities, densities, quantiles, and moments. Probabilistic residuals and scoring via log-score (or log-likelihood), (continuous) ranked probability score, etc. Diagnostic graphics like rootograms, PIT histograms, (randomized) quantile residual Q-Q plots, and reliagrams (reliability diagrams).

Authors:Achim Zeileis [aut, cre], Moritz N. Lang [aut], Reto Stauffer [aut], Christian Kleiber [ctb], Ioannis Kosmidis [ctb], Jakob Messner [ctb]

topmodels_0.3-0.tar.gz
topmodels_0.3-0.zip(r-4.7)topmodels_0.3-0.zip(r-4.6)topmodels_0.3-0.zip(r-4.5)
topmodels_0.3-0.tgz(r-4.6-x86_64)topmodels_0.3-0.tgz(r-4.6-arm64)topmodels_0.3-0.tgz(r-4.5-x86_64)topmodels_0.3-0.tgz(r-4.5-arm64)
topmodels_0.3-0.tar.gz(r-4.7-arm64)topmodels_0.3-0.tar.gz(r-4.7-x86_64)topmodels_0.3-0.tar.gz(r-4.6-arm64)topmodels_0.3-0.tar.gz(r-4.6-x86_64)
topmodels_0.3-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
topmodels/json (API)
NEWS

# Install 'topmodels' in R:
install.packages('topmodels', repos = c('https://zeileis.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://r-forge.r-project.org/projects/topmodels

Datasets:

On CRAN:

Conda:

3.86 score 1 packages 43 scripts 61 exports 19 dependencies

Last updated from:0325f4bb38. Checks:13 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK208
linux-devel-x86_64OK207
source / vignettesOK215
linux-release-arm64OK201
linux-release-x86_64OK201
macos-release-arm64OK186
macos-release-x86_64OK289
macos-oldrel-arm64OK119
macos-oldrel-x86_64OK600
windows-develOK222
windows-releaseOK197
windows-oldrelOK215
wasm-releaseOK120

Exports:crps.distributiondempiricalEmpiricalgeom_pithistgeom_pithist_confintgeom_pithist_expectedgeom_pithist_simintgeom_qqrplotgeom_qqrplot_confintgeom_qqrplot_refgeom_qqrplot_simintgeom_rootogramgeom_rootogram_confintgeom_rootogram_expectedgeom_rootogram_refGeomPithistGeomPithistConfintGeomPithistExpectedGeomPithistSimintGeomQqrplotGeomQqrplotConfintGeomQqrplotRefGeomQqrplotSimintGeomRootogramGeomRootogramConfintGeomRootogramExpectedGeomRootogramRefnewresponsepempiricalpithistprocastpromodelproresidualsproscoreqempiricalqqrplotreliagramrempiricalrootogramstat_pithiststat_pithist_confintstat_pithist_expectedstat_pithist_simintstat_qqrplot_confintstat_qqrplot_refstat_qqrplot_simintstat_rootogramstat_rootogram_confintstat_rootogram_expectedStatPithistStatPithistConfintStatPithistExpectedStatPithistSimintStatQqrplotConfintStatQqrplotRefStatQqrplotSimintStatRootogramStatRootogramConfintStatRootogramExpectedtopmodelswormplot

Dependencies:clicolorspacecpp11distributions3farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Method for Numerically Evaluating the CRPS of Probability Distributionscrps.BAMLSS crps.Bernoulli crps.Beta crps.Binomial crps.distribution crps.Erlang crps.Exponential crps.GAMLSS crps.Gamma crps.Geometric crps.GEV crps.Gumbel crps.HyperGeometric crps.Logistic crps.LogNormal crps.NegativeBinomial crps.Normal crps.Poisson crps.StudentsT crps.Uniform crps.XBetaX
Method for Numerically Evaluate Central Moments of Probability Distributionsdistribution_calculate_moments kurtosis.distribution mean.distribution random.distribution skewness.distribution variance.distribution
Create an Empirical Distributioncdf.Empirical dempirical Empirical kurtosis.Empirical log_pdf.Empirical mean.Empirical pdf.Empirical pempirical qempirical quantile.Empirical random.Empirical rempirical skewness.Empirical support.Empirical variance.Empirical
'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with `ggplot2`GeomQqrplot GeomQqrplotConfint GeomQqrplotRef GeomQqrplotSimint geom_qqrplot geom_qqrplot_confint geom_qqrplot_ref geom_qqrplot_simint StatQqrplotConfint StatQqrplotRef StatQqrplotSimint stat_qqrplot_confint stat_qqrplot_ref stat_qqrplot_simint
Extract Observed Responses from New Datanewresponse newresponse.default newresponse.distribution newresponse.glm
Methods for Numerically Approximating PDF and Quantile Functionscdf.distribution pdf.distribution quantile.distribution
PIT Histograms for Assessing Goodness of Fit of Probability Modelsc.pithist pithist pithist.default rbind.pithist
S3 Methods for Plotting PIT Histogramsautoplot.pithist lines.pithist plot.pithist
S3 Methods for Plotting Q-Q Residuals Plotsautoplot.qqrplot plot.qqrplot points.qqrplot
S3 Methods for a Reliagram (Extended Reliability Diagram)autoplot.reliagram lines.reliagram plot.reliagram
S3 Methods for Plotting Rootogramsautoplot.rootogram plot.rootogram
Procast: Probabilistic Forecastingprocast procast.bamlss procast.default procast.disttree procast.glm procast.lm
Predictions and Residuals Dispatch for Probabilistic Modelspredict.promodel promodel residuals.promodel
Residuals for Probabilistic Regression Modelsproresiduals proresiduals.default
Scoring Probabilistic Forecastsproscore proscore.default
Q-Q Plots for Quantile Residualsc.qqrplot qqrplot qqrplot.default
Reliagram (Extended Reliability Diagram)c.reliagram reliagram reliagram.default
Rootograms for Assessing Goodness of Fit of Probability Modelsc.rootogram rbind.rootogram rootogram rootogram.default
Serum Potassium LevelsSerumPotassium
'geom_*' and 'stat_*' for Producing PIT Histograms with `ggplot2`GeomPithist GeomPithistConfint GeomPithistExpected GeomPithistSimint geom_pithist geom_pithist_confint geom_pithist_expected geom_pithist_simint StatPithist StatPithistConfint StatPithistExpected StatPithistSimint stat_pithist stat_pithist_confint stat_pithist_expected stat_pithist_simint
'geom_*' and 'stat_*' for Producing Rootograms with `ggplot2`GeomRootogram GeomRootogramConfint GeomRootogramExpected GeomRootogramRef geom_rootogram geom_rootogram_confint geom_rootogram_expected geom_rootogram_ref StatRootogram StatRootogramConfint StatRootogramExpected stat_rootogram stat_rootogram_confint stat_rootogram_expected
Plotting Graphical Evaluation Tools for Probabilistic Modelstopmodels
Tukey's Volcano HeightsVolcanoHeights
Worm Plots for Quantile Residualswormplot wormplot.default