gencve (version 0.3)

yhat_lars: Fit LASSO Regression using Mallows Cp and Predict

Description

LASSO regression is fit using the lars algorithm

Usage

yhat_lars(dfTrain, dfTest, normalize = TRUE)

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.

normalize

Default TRUE means the predictors are centered and scaled. Otherwise no transformation.

Value

Examples

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_lars(trdf, tedf)