forc.ecdf: Empirical CDF computations for posterior forecast samples
Description
Computes (pointwise over time) empirical density (error bands) and
mean forecasts for a Monte Carlo or Bayesian posterior sample of forecasts.
Usage
forc.ecdf(forecasts, probs = c(0.05, 0.95), start = c(0, 1), ...)
Arguments
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
Value
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.
Details
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.