forc.ecdf {MSBVAR} | R Documentation |
Computes (pointwise over time) empirical density (error bands) and mean forecasts for a Monte Carlo or Bayesian posterior sample of forecasts.
forc.ecdf(forecasts, probs = c(0.05, 0.95), start = c(0, 1), ...)
forecasts |
Posterior sample of VAR forecasts produced by
hc.forecast.VAR() or uc.forecast.VAR() |
probs |
Error band width in percentiles, default is 90% error band. |
start |
Start value for the time series – as in the ts()
for the forecast horizon |
... |
Other ecdf() parameters |
For each endogenous variable in the VAR and each point in the forecast
horizon this function estimates the percentile based confidence
interval. It then returns a time series matrix beginning at
start
of the mean forecast and the limits of the confidence
region for each variable in the forecast sample.
A multiple time series object is returned where the first column is the mean estimate followed by the upper and lower bounds of the confidence region.
Patrick T. Brandt