cleaning.lm: Cleaning.lm

In jbecu/ridgeAdap: Adaptive Ridge for variable selection

Description

Cleaning.lm

Usage

cleaning.lm(X,y,screening=NULL,beta=rep(1,ncol(X)),test="student",
group=1:ncol(X),scale=FALSE,center=TRUE)

Arguments

X	a matrix object with n*p size representing the data
y	a vector of size p representing the output variable
screening	object issued from the screening or screening.group functions. If is not NULL then the beta.min vector contained in this object will be used instead the beta main parameter.
beta	a vector of size p representing the weight of variable. A variable with weight equal to zero signify will not appear in the ordinary least square regression. The number of variables with a non-zero weight must be inferious to the sample size of X.
test	a string of characters to determine the statistical test to be used. This should be one of "student" or "fisher". Student or fisher test are the same when variables are not grouped. If variables are grouped then the student t-test measure the significancy of each variables and the fisher F-test measure the significancy of each groups of variables. Default is "student".
group	a vector of size p representing the group index for each variables. Default is 1:ncol(X) which represent the particular case whit no group. Warning : variables and this vector must be in ascending group order.
scale	a boolean to indicate if X and y will be scaled. Default is FALSE.
center	a boolean to indicate if X and y will be centered. Default is TRUE.

Value

An object of class 'cleaning' with pvalue for each variables or group variables corresponding to the satistical test choice. Contain equally estimates of ols and t or F statistics.

Author(s)

JM BECU

Examples

 # see ridgeAdap help

jbecu/ridgeAdap documentation built on May 18, 2019, 5:58 p.m.