rvi: Extracts Relative Variable Importances from 'fDMA' Model.

In fDMA: Dynamic Model Averaging and Dynamic Model Selection for Continuous Outcomes

Extracts Relative Variable Importances from fDMA Model.

Description

This functions extracts posterior inclusion probabilities for independent variables from dma object.

Usage

rvi(dma.object)

Arguments

dma.object

dma object

Value

matrix of posterior inclusion probabilities for independent variables

Examples

wti <- crudeoil[-1,1]
drivers <- (lag(crudeoil[,-1],k=1))[-1,]
ld.wti <- (diff(log(wti)))[-1,]
ld.drivers <- drivers[-1,]
ld.drivers[,c(4,6)] <- (diff(drivers[,c(4,6)]))[-1,]
ld.drivers[,c(1:2,5,7)] <- (diff(log(drivers[,c(1:2,5,7)])))[-1,]
ld.drivers[,c(3,6)] <- ld.drivers[,c(3,6)]/100
m1 <- fDMA(y=ld.wti,x=ld.drivers,alpha=0.99,lambda=0.90,initvar=10)
r <- rvi(m1)

fDMA documentation built on April 4, 2025, 5:16 a.m.