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:
topmodels_0.3-0.tar.gz
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topmodels_0.3-0.tgz(r-4.4-x86_64)topmodels_0.3-0.tgz(r-4.4-arm64)topmodels_0.3-0.tgz(r-4.3-x86_64)topmodels_0.3-0.tgz(r-4.3-arm64)
topmodels_0.3-0.tar.gz(r-4.5-noble)topmodels_0.3-0.tar.gz(r-4.4-noble)
topmodels_0.3-0.tgz(r-4.4-emscripten)topmodels_0.3-0.tgz(r-4.3-emscripten)
topmodels.pdf |topmodels.html✨
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
- SerumPotassium - Serum Potassium Levels
- VolcanoHeights - Tukey's Volcano Heights
Last updated 1 months agofrom:81645b17c5. Checks:OK: 3 NOTE: 6. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 20 2024 |
R-4.5-win-x86_64 | OK | Nov 20 2024 |
R-4.5-linux-x86_64 | OK | Nov 20 2024 |
R-4.4-win-x86_64 | NOTE | Nov 20 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 20 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 20 2024 |
R-4.3-win-x86_64 | NOTE | Nov 20 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 20 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 20 2024 |
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:clicolorspacedistributions3fansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Method for Numerically Evaluating the CRPS of Probability Distributions | crps.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 |
Create an Empirical Distribution | cdf.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 Data | newresponse newresponse.default newresponse.distribution newresponse.glm |
PIT Histograms for Assessing Goodness of Fit of Probability Models | c.pithist pithist pithist.default rbind.pithist |
S3 Methods for Plotting PIT Histograms | autoplot.pithist lines.pithist plot.pithist |
S3 Methods for Plotting Q-Q Residuals Plots | autoplot.qqrplot plot.qqrplot points.qqrplot |
S3 Methods for a Reliagram (Extended Reliability Diagram) | autoplot.reliagram lines.reliagram plot.reliagram |
S3 Methods for Plotting Rootograms | autoplot.rootogram plot.rootogram |
Procast: Probabilistic Forecasting | procast procast.bamlss procast.default procast.disttree procast.glm procast.lm |
Predictions and Residuals Dispatch for Probabilistic Models | predict.promodel promodel residuals.promodel |
Residuals for Probabilistic Regression Models | proresiduals proresiduals.default |
Scoring Probabilistic Forecasts | proscore proscore.default |
Q-Q Plots for Quantile Residuals | c.qqrplot qqrplot qqrplot.default |
Reliagram (Extended Reliability Diagram) | c.reliagram reliagram reliagram.default |
Rootograms for Assessing Goodness of Fit of Probability Models | c.rootogram rbind.rootogram rootogram rootogram.default |
Serum Potassium Levels | SerumPotassium |
'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 Models | topmodels |
Tukey's Volcano Heights | VolcanoHeights |
Worm Plots for Quantile Residuals | wormplot wormplot.default |