fvauto: Vector autoregressive approximation

In gausscov: The Gaussian Covariate Method for Variable Selection

Vector autoregressive approximation

Description

Vector autoregressive approximation

Usage

fvauto(x,n,omx,p0=0.01,kmn=0,kmx=0,mx=21,kex=0,sub=T,inr=TRUE)

Arguments

x	Variable
n	Sample size
omx	Maximum lag
p0	The P-value cut-off
kmn	Minimum number of included covariates irrespective of cut-off P-value
kmx	Maxmum number of included covariates irrespective of cut-off P-value
mx	The maximum number covariates for an all subset search
kex	The excluded covariates
sub	Logical, if TRUE best subset selected
inr	Logical, if TRUE include intercept if not present

Value

res The selected lagged variables for each variable res2 The regression coefficients and P-values res4 The residuals

Examples

data(abcq)
 a<-fvauto(abcq,240,16)

gausscov documentation built on Oct. 12, 2023, 1:06 a.m.