standardize: Standardizes the input design matrix X and output vector Y to...

In Saptati-Datta/AdapLasso: Computes Adaptive Lasso Using Lars Algorithm

Description

Standardizes the input design matrix X and output vector Y to mean 0 and scales X

Usage

standardize(X, Y, gamma)

Arguments

X	n x p design matrix of inputs
Y	n x 1 vector of outputs
gamma	a scalar(>0) input used in the weight(user input)

Value

Xstd	scaled X
Ystd	scaled Y
meanY	mean of Y
meanX	Column means after centering the weighted X matrix from scale_X
weights	weights obtained by centering X_w which is obtained from scale X

Examples

X <- matrix(rnorm(500), 50, 10)
Y <- rnorm(50)
gamma <- 2
#Standardizing X and Y
std <- standardize(X , Y , gamma)
#Deriving weighted and centered design matrix
Xstd <- std$Xstd
#Column means of centered X_w
meanX <- std$meanX
#Deriving centered Y
Ystd <- std$Ystd
#Mean of Ystd
meanY <- std$meanY
# Weights
weights <- std$weights

Saptati-Datta/AdapLasso documentation built on Dec. 18, 2021, 12:57 p.m.