Function reference • topmodels

Procast infrastructure
`procast()`	Procast: Probabilistic Forecasting
`proresiduals()`	Residuals for Probabilistic Regression Models
`proscore()`	Scoring Probabilistic Forecasts
`promodel()` `residuals(<promodel>)` `predict(<promodel>)`	Predictions and Residuals Dispatch for Probabilistic Models
`newresponse()`	Extract Observed Responses from New Data
`crps.distribution()` `crps.Beta()` `crps.Bernoulli()` `crps.Binomial()` `crps.Erlang()` `crps.Exponential()` `crps.Gamma()` `crps.GEV()` `crps.Geometric()` `crps.Gumbel()` `crps.HyperGeometric()` `crps.Logistic()` `crps.LogNormal()` `crps.NegativeBinomial()` `crps.Normal()` `crps.Poisson()` `crps.StudentsT()` `crps.Uniform()` `crps.XBetaX()` `crps.GAMLSS()` `crps.BAMLSS()`	Method for Numerically Evaluating the CRPS of Probability Distributions
Probabilistic model diagnostics
`rootogram()`	Rootograms for Assessing Goodness of Fit of Probability Models
`pithist()`	PIT Histograms for Assessing Goodness of Fit of Probability Models
`qqrplot()`	Q-Q Plots for Quantile Residuals
`wormplot()`	Worm Plots for Quantile Residuals
`reliagram()`	Reliagram (Extended Reliability Diagram)
Plotting probabilistic model diagnostics
`plot(<rootogram>)` `autoplot(<rootogram>)`	S3 Methods for Plotting Rootograms
`plot(<pithist>)` `lines(<pithist>)` `autoplot(<pithist>)`	S3 Methods for Plotting PIT Histograms
`plot(<qqrplot>)` `points(<qqrplot>)` `autoplot(<qqrplot>)`	S3 Methods for Plotting Q-Q Residuals Plots
`plot(<reliagram>)` `lines(<reliagram>)` `autoplot(<reliagram>)`	S3 Methods for a Reliagram (Extended Reliability Diagram)
`stat_rootogram()` `geom_rootogram()` `stat_rootogram_expected()` `geom_rootogram_expected()` `GeomRootogramExpected` `geom_rootogram_ref()` `stat_rootogram_confint()` `geom_rootogram_confint()`	`geom_` and `stat_` for Producing PIT Histograms with `ggplot2`
`stat_pithist()` `geom_pithist()` `stat_pithist_expected()` `geom_pithist_expected()` `stat_pithist_confint()` `geom_pithist_confint()` `stat_pithist_simint()` `geom_pithist_simint()`	`geom_` and `stat_` for Producing PIT Histograms with `ggplot2`
`geom_qqrplot()` `stat_qqrplot_simint()` `geom_qqrplot_simint()` `stat_qqrplot_ref()` `geom_qqrplot_ref()` `geom_qqrplot_confint()` `GeomQqrplotConfint`	`geom_` and `stat_` for Producing Quantile Residual Q-Q Plots with `ggplot2`
`topmodels()`	Plotting Graphical Evaluation Tools for Probabilistic Models
Interfacs to models/distributions
`Empirical()` `pempirical()` `dempirical()` `qempirical()` `rempirical()` `mean(<Empirical>)` `variance(<Empirical>)` `skewness(<Empirical>)` `kurtosis(<Empirical>)` `random(<Empirical>)` `pdf(<Empirical>)` `log_pdf(<Empirical>)` `cdf(<Empirical>)` `quantile(<Empirical>)` `support(<Empirical>)`	Create an Empirical distribution
Data sets
`SerumPotassium`	Serum Potassium Levels
`VolcanoHeights`	Tukey's Volcano Heights

Reference

Procast infrastructure

Probabilistic model diagnostics

Plotting probabilistic model diagnostics

Interfacs to models/distributions

Data sets