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perry (version 0.1.1)

Resampling-based prediction error estimation for regression models

Description

Tools that allow developers to write functions for prediction error estimation with minimal programming effort and assist users with model selection in regression problems.

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Version

Install

install.packages('perry')

Monthly Downloads

1,011

Version

0.1.1

License

GPL (>= 2)

Maintainer

Andreas Alfons

Last Published

September 9th, 2012

Functions in perry (0.1.1)

aggregate.perry

Aggregate resampling-based prediction error results
fortify.perry

Convert resampling-based prediction error results into a data frame for plotting
bootPE

Bootstrap prediction error estimation for fitted models
perryFit

Resampling-based prediction error for model evaluation
bootSamples

Bootstrap samples
subset.perry

Subsetting resampling-based prediction error results
bootControl

Control object for bootstrap samples
perryTuning

Resampling-based prediction error for tuning parameter selection
perry

Resampling-based prediction error for fitted models
perryReshape

Reshape resampling-based prediction error results
perrySelect

Model selection via resampling-based prediction error measures
repRS

(Repeated) random splitting for fitted models
cost

Prediction loss
cvFolds

Cross-validation folds
perryPlot

Plot resampling-based prediction error results
perrySplits

Data splits for resampling-based prediction error measures
splitControl

Control object for random data splits
reperry

Recompute resampling-based prediction error measures
accessors

Access or set information on resampling-based prediction error results
foldControl

Control object for cross-validation folds
summary.perry

Summarize resampling-based prediction error results
randomSplits

Random data splits
perry-package

Resampling-based prediction error estimation for regression models
repCV

(Repeated) cross-validation for fitted models