ShamanStine.PI {BootPR} | R Documentation |
The function returns bias-corrected forecasts and bootstrap prediction intervals using Shaman and Stine bias formula for univariate AR models
ShamanStine.PI(x, p, h, nboot, prob, type, correct, pmax)
x |
a time series data set |
p |
AR order |
h |
the number of forecast periods |
nboot |
number of bootstrap iterations |
prob |
a vector of probability values |
type |
"const" for the AR model with intercept only, "const+trend" for the AR model with intercept and trend |
correct |
"kilian" for Kilian's stationarity-correction; "ssf" for stationarity-correction based on stable spectral factorization |
pmax |
for exogenous lag order algorithm, pmax = 0, for endogenous lag order algorithm, pmax is an integer greater than 0 |
PI |
prediction intervals |
forecast |
bias-corrected point forecasts |
Contact the author for the details of the stationarity-correction based on stable spectral factorization
Jae H. Kim
Kim, J.H., 2004, Bootstrap Prediction Intervals for Autoregression using Asymptotically Mean-Unbiased Parameter Estimators, International Journal of Forecasting, 20, 85-97.
Kim, J.H., 2003, Forecasting Autoregressive Time Series with Bias-Corrected Parameter Estimators, International Journal of Forecasting, 19, 493-502.
Shaman, P., & Stine, R. A. (1988). The bias of autoregressive coefficient estimators. Journal of the American Statistical Association, 83, 842-848.
Stine, R. A., & Shaman, P. (1989). A fixed point characterization for bias of autoregressive estimators. The Annals of Statistics,17, 1275-1284.
Kilian, L. (1998a). Small sample confidence intervals for impulse response functions. The Review of Economics and Statistics, 80,218-230.
data(IPdata) ShamanStine.PI(IPdata,p=6,h=10,nboot=1000,prob=c(0.5,0.95),type="const+trend",correct="ssf",pmax=0)