fgr1st: Calculates a dependence graph using Gaussian stepwise... In gausscov: The Gaussian Covariate Method for Variable Selection

Description

Calculates an independence graph using Gaussian stepwise selection

Usage

 1 fgr1st(x,p0=0.01,ind=0,nu=1,kmn=0,kmx=0,nedge=10^5,inr=T,xinr=F)

Arguments

 x The 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 selected variables for each node irrespective of cut-off P-value kmx The maximum number 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 together with P-values for each edge and proportional reduction of sum of squared residuals.

Examples

 1 2 data(boston) a<-fgr1st(,1:13],ind=3:6)

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