bestglm: grpregPredict – R documentation

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grpregPredict

Predictions on Test Data with Grpreg

Description

A dataframe is partitioned randomly into training and test samples. The function grpreg::grpreg() is used to fit the training data using Lasso, SCAD and MCP penalty functions. The BIC criterion is used to selecting the penalty parameter lambda.

Usage

grpregPredict(Xy, trainFrac = 2/3, XyList=NULL)

Arguments

`Xy`	a dataframe that may contain factor variables
`trainFrac`	the fraction of data to be used for training
`XyList`	instead of supplying Xy you can provide XyList.

Value

vector of RMSEs

Examples

grpregPredict(mcdonald)

bestglm

Best Subset GLM and Regression Utilities

v0.37.3

GPL (>= 2)

Authors

A.I. McLeod, Changjiang Xu and Yuanhao Lai

Initial release

2020-03-13