OSA: The OSA gives a simple average estimatoris by averaging all...

In LIC: The LIC Criterion for Optimal Subset Selection

The OSA gives a simple average estimatoris by averaging all these least squares estimators.

Description

The OSA gives a simple average estimatoris by averaging all these least squares estimators.

Usage

OSA(X, Y, alpha, K, nk)

Arguments

X	is a design matrix
Y	is a random response vector of observed values
alpha	is the significance level
K	is the number of subsets
nk	is the sample size of subsets

Value

MUA,BetaA,MAEMUA,MSEMUA

Examples

set.seed(12)
X=matrix(data=sample(1:3,1200*5, replace = TRUE) ,nrow=1200,ncol=5)  
b=sample(1:3,5, replace = TRUE)         
e= rnorm(1200, 0, 1)    
Y=X%*%b+e
alpha=0.05	
K=10
nk=1200/K 
OSA(X,Y,alpha,K,nk)

LIC documentation built on March 28, 2022, 9:12 a.m.