fgr1st: Calculates a dependence graph using Gaussian stepwise...

In gausscov: The Gaussian Covariate Method for Variable Selection

Calculates a dependence graph using Gaussian stepwise selection

Description

Calculates an independence graph using Gaussian stepwise selection

Usage

fgr1st(x,p0=0.01,ind=0,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
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

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

gausscov documentation built on Feb. 16, 2023, 6:52 p.m.