VAR.BPR {VAR.etp} | R 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
[Package VAR.etp version 1.1 Index]