IterGS: Iterative graphlet screening procedure

In ScreenClean: Screen and clean variable selection procedures

Description

The iterative graphlet screening procedure, main function of the package.

Usage

IterGS(y.tilde, gram, gram.bias, cg.all, sp, tau, nm, q0=0.1, scale = 1, max.iter = 3, 
std.thresh = 1.05, beta.initial = NULL)

Arguments

y.tilde	X'y where X and y are the predictor matrix and the response vector, respectively.
gram	the threholded gram matrix
gram.bias	the bias of the threholded gram matrix
cg.all	all the connected cg.alls of gram with size no more than nm.
sp	the expected sparse level
tau	the minimal signal strength to be detected
nm	the maximal size of the connected subgaphs considered in the screening step.
q0	the minimal screening parameter
scale	optional numerical parameter of the screening step. The default is 1
max.iter	the maximal number of iterations. The default is 3.
std.thresh	the threshold of the std change that stop the loop. The default is 1.05.
beta.initial	the initial estimate of beta in reducing the bias. The default is uu*sign(y.tilde)*(abs(y.tilde)>uu).

Value

IterGS returns a list with two elements

estimate	The iterative GS estimate of beta
n.iter	The number of iterations it takes

Examples

##See demoIterGs.r

ScreenClean documentation built on May 2, 2019, 9:27 a.m.