fgr2st: Calculates an independence graph using repeated stepwise... In gausscov: The Gaussian Covariate Method for Variable Selection

Description

Calculates a dependency graph using repeated Gaussian stepwise selection

Usage

 1 fgr2st(x,p0=0.01,ind=0,nu=1,kmn=0,kmx=0,nedge=10^5,inr=T,xinr=F)

Arguments

 x Matrix of covariates p0 Cut-off P-value ind Restricts the dependent nodes to this subset nu The order statistic of Gaussian covariates used for comparison. kmn The minimum number of selected variables for each node irrespective of cut-off P-value kmx The maximum number of selected variables for each node irrespective of cut-off P-value nedge Maximum number of edges inr Logical, if TRUE include an intercept xinr Logical, if TRUE intercept already included

Value

ned Number of edges

edg List of edges giving nodes (covariates), the approximations for each node, the covariates in the approximation and the corresponding P-values.

Examples

 1 2 data(redwine) a<-fgr2st(,1:11],ind=4:8)

gausscov documentation built on Jan. 17, 2022, 9:06 a.m.