Infrastructure for Forecasting and Assessment of Probabilistic Models


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Documentation for package ‘topmodels’ version 0.3-0

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A C D E G K L M N P Q R S T V W

-- A --

autoplot.pithist S3 Methods for Plotting PIT Histograms
autoplot.qqrplot S3 Methods for Plotting Q-Q Residuals Plots
autoplot.reliagram S3 Methods for a Reliagram (Extended Reliability Diagram)
autoplot.rootogram S3 Methods for Plotting Rootograms

-- C --

c.pithist PIT Histograms for Assessing Goodness of Fit of Probability Models
c.qqrplot Q-Q Plots for Quantile Residuals
c.reliagram Reliagram (Extended Reliability Diagram)
c.rootogram Rootograms for Assessing Goodness of Fit of Probability Models
cdf.Empirical Create an Empirical distribution
crps.BAMLSS Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Bernoulli Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Beta Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Binomial Method for Numerically Evaluating the CRPS of Probability Distributions
crps.distribution Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Erlang Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Exponential Method for Numerically Evaluating the CRPS of Probability Distributions
crps.GAMLSS Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Gamma Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Geometric Method for Numerically Evaluating the CRPS of Probability Distributions
crps.GEV Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Gumbel Method for Numerically Evaluating the CRPS of Probability Distributions
crps.HyperGeometric Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Logistic Method for Numerically Evaluating the CRPS of Probability Distributions
crps.LogNormal Method for Numerically Evaluating the CRPS of Probability Distributions
crps.NegativeBinomial Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Normal Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Poisson Method for Numerically Evaluating the CRPS of Probability Distributions
crps.StudentsT Method for Numerically Evaluating the CRPS of Probability Distributions
crps.Uniform Method for Numerically Evaluating the CRPS of Probability Distributions
crps.XBetaX Method for Numerically Evaluating the CRPS of Probability Distributions

-- D --

dempirical Create an Empirical distribution

-- E --

Empirical Create an Empirical distribution

-- G --

GeomPithist 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomPithistConfint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomPithistExpected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomPithistSimint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomQqrplot 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
GeomQqrplotConfint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
GeomQqrplotRef 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
GeomQqrplotSimint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
GeomRootogram 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomRootogramConfint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomRootogramExpected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
GeomRootogramRef 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_pithist 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_pithist_confint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_pithist_expected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_pithist_simint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_qqrplot 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
geom_qqrplot_confint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
geom_qqrplot_ref 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
geom_qqrplot_simint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
geom_rootogram 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_rootogram_confint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_rootogram_expected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
geom_rootogram_ref 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'

-- K --

kurtosis.Empirical Create an Empirical distribution

-- L --

lines.pithist S3 Methods for Plotting PIT Histograms
lines.reliagram S3 Methods for a Reliagram (Extended Reliability Diagram)
log_pdf.Empirical Create an Empirical distribution

-- M --

mean.Empirical Create an Empirical distribution

-- N --

newresponse Extract Observed Responses from New Data
newresponse.default Extract Observed Responses from New Data
newresponse.distribution Extract Observed Responses from New Data
newresponse.glm Extract Observed Responses from New Data

-- P --

pdf.Empirical Create an Empirical distribution
pempirical Create an Empirical distribution
pithist PIT Histograms for Assessing Goodness of Fit of Probability Models
pithist.default PIT Histograms for Assessing Goodness of Fit of Probability Models
plot.pithist S3 Methods for Plotting PIT Histograms
plot.qqrplot S3 Methods for Plotting Q-Q Residuals Plots
plot.reliagram S3 Methods for a Reliagram (Extended Reliability Diagram)
plot.rootogram S3 Methods for Plotting Rootograms
points.qqrplot S3 Methods for Plotting Q-Q Residuals Plots
predict.promodel Predictions and Residuals Dispatch for Probabilistic Models
procast Procast: Probabilistic Forecasting
procast.bamlss Procast: Probabilistic Forecasting
procast.default Procast: Probabilistic Forecasting
procast.disttree Procast: Probabilistic Forecasting
procast.glm Procast: Probabilistic Forecasting
procast.lm Procast: Probabilistic Forecasting
promodel Predictions and Residuals Dispatch for Probabilistic Models
proresiduals Residuals for Probabilistic Regression Models
proresiduals.default Residuals for Probabilistic Regression Models
proscore Scoring Probabilistic Forecasts
proscore.default Scoring Probabilistic Forecasts

-- Q --

qempirical Create an Empirical distribution
qqrplot Q-Q Plots for Quantile Residuals
qqrplot.default Q-Q Plots for Quantile Residuals
quantile.Empirical Create an Empirical distribution

-- R --

random.Empirical Create an Empirical distribution
rbind.pithist PIT Histograms for Assessing Goodness of Fit of Probability Models
rbind.rootogram Rootograms for Assessing Goodness of Fit of Probability Models
reliagram Reliagram (Extended Reliability Diagram)
reliagram.default Reliagram (Extended Reliability Diagram)
rempirical Create an Empirical distribution
residuals.promodel Predictions and Residuals Dispatch for Probabilistic Models
rootogram Rootograms for Assessing Goodness of Fit of Probability Models
rootogram.default Rootograms for Assessing Goodness of Fit of Probability Models

-- S --

SerumPotassium Serum Potassium Levels
skewness.Empirical Create an Empirical distribution
StatPithist 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
StatPithistConfint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
StatPithistExpected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
StatPithistSimint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
StatQqrplotConfint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
StatQqrplotRef 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
StatQqrplotSimint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
StatRootogram 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
StatRootogramConfint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
StatRootogramExpected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_pithist 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_pithist_confint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_pithist_expected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_pithist_simint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_qqrplot_confint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
stat_qqrplot_ref 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
stat_qqrplot_simint 'geom_*' and 'stat_*' for Producing Quantile Residual Q-Q Plots with 'ggplot2'
stat_rootogram 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_rootogram_confint 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
stat_rootogram_expected 'geom_*' and 'stat_*' for Producing PIT Histograms with 'ggplot2'
support.Empirical Create an Empirical distribution

-- T --

topmodels Plotting Graphical Evaluation Tools for Probabilistic Models

-- V --

variance.Empirical Create an Empirical distribution
VolcanoHeights Tukey's Volcano Heights

-- W --

wormplot Worm Plots for Quantile Residuals
wormplot.default Worm Plots for Quantile Residuals