VAR.BPR: Bootstrap Prediction Intervals for VAR(p) Model

View source: R/VAR.BPR.R

VAR.BPRR Documentation

Bootstrap Prediction Intervals for VAR(p) Model

Description

No Bias-correction is given

Usage

VAR.BPR(x, p, h, nboot = 500, type = "const", alpha = 0.95)

Arguments

x

data matrix in column

p

AR order

h

forecasting period

nboot

number of bootstrap iterations

type

"const" for the AR model with intercept only, "const+trend" for the AR model with intercept and trend

alpha

100(1-alpha) percent prediction intervals

Details

Bootstrap Prediction Intervals for VAR(p) Model

Value

Intervals

Prediction Intervals

Forecast

Point Forecasts

alpha

Probability Content of Prediction Intervals

Note

No Bias-correction is given

Author(s)

Jae H. Kim

References

Kim, J. H. (2001). Bootstrap-after-bootstrap prediction intervals for autoregressive models, Journal of Business & Economic Statistics, 19, 117-128.

Examples

data(dat)
VAR.BPR(dat,p=2,h=10,nboot=200,type="const",alpha=0.95)
# nboot is set to a low number for fast execution in the example
# In actual implementation, use higher number such as nboot=1000

VAR.etp documentation built on July 2, 2022, 1:05 a.m.