VARpred: VAR Prediction

In MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

VAR Prediction

Description

Computes the forecasts of a VAR model, the associated standard errors of forecasts and the mean squared errors of forecasts

Usage

VARpred(model, h = 1, orig = 0, Out.level = FALSE, output = TRUE)

Arguments

model	An output object of a VAR or refVAR command
h	Forecast horizon, a positive integer
orig	Forecast origin. Default is zero meaning the forecast origin is the last data point
Out.level	Boolean control for details of output
output	Boolean control for printing forecast results

Details

Computes point forecasts and the associated variances of forecast errors

Value

pred	Point predictions
se.err	Standard errors of the predictions
mse	Mean-square errors of the predictions

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 2). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Examples

data("mts-examples",package="MTS")
gdp=log(qgdp[,3:5])
zt=diffM(gdp)
m1=VAR(zt,p=2)
VARpred(m1,4)

MTS documentation built on April 11, 2022, 5:07 p.m.