gencve (version 0.3)

yhat_plus: SCAD or MCP Regression Prediction

Description

Fits penalized regression with SCAD or MCP penalty and computes the predictions for the test data.

Usage

yhat_plus(dfTrain, dfTest, normalize = TRUE, ic = c("BIC", "AIC"), 
		method = c("scad", "mc+", "lasso"))

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.

ic

"AIC" or "BIC"

method

"scad", "mc+" or "lasso"

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_plus(trdf, tedf)