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

In VAR.etp: VAR Modelling: Estimation, Testing, and Prediction

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 Aug. 31, 2023, 9:08 a.m.