yhat_step: Backward Stagewise Regression with AIC or BIC

Description Usage Arguments Value Author(s) Examples

View source: R/yhat_step.R

Description

Fits a subset regression model using backward stagewise regression to training data and computes the predictions for the test data.

Usage

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yhat_step(dfTrain, dfTest, ic = c("BIC", "AIC"))

Arguments

dfTrain

Data frame for training data. Last column must be the output variable.

dfTest

Data frame for test data. Last column must be the output variable.

ic

Information criterion to use to select the number of components. Default is BIC.

Value

The predictions for the test sample

Author(s)

A. I. McLeod

Examples

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Xy <- prostate
X <- prostate[,-9]
y <- prostate[,9]
n <- length(y)
d <- 10
set.seed(777513)
iTe <- sample(n, size=d)
iTr <- (1:n)[!match(1:n, iTe, nomatch = 0) > 0]
trdf <- data.frame(X[iTr,], y=y[iTr]) #X, y already defined
tedf <- data.frame(X[iTe,], y=y[iTe])
yhat_step(trdf, tedf)

gencve documentation built on May 29, 2017, 7:12 p.m.