| plot.forc.ecdf {MSBVAR} | R Documentation |
Plots mean VAR forecasts and pointwise error bands
plot.forc.ecdf(x, probs = c(0.05, 0.95),
xlab = "", ylab = "", ylim = NA, ...)
x |
N x nstep matrix of forecasts |
probs |
width of error band probabilities, default is 90% quantiles or
c(0.05,0.95) |
xlab |
x-axis labels |
ylab |
y-axis labels |
ylim |
Bounds for y-axis in standard format c(lower,upper) |
... |
other plot parameters |
Plots the mean forecast and the pointwise empirical confidence region for a posterior sample of VAR forecasts.
None.
Patrick T. Brandt
## Not run:
data(IsraelPalestineConflict)
# Fit a BVAR model
fit.BVAR <- szbvar(IsraelPalestineConflict, p=6, z=NULL, lambda0=0.6,
lambda1=0.1, lambda3=2, lambda4=0.5, lambda5=0,
mu5=0, mu6=0, nu=3, qm=4, prior=0,
posterior.fit=FALSE)
# Generate unconditional forecasts for both models
forecast.BVAR <- uc.forecast(fit.BVAR, nsteps=12,
burnin=100, gibbs=1000)
# Plot the forecasts
par(mfrow=c(2,1))
plot(forecast.BVAR$forecast[,,1], probs=c(0.16,0.84),
main="I2P Forecast")
abline(h=0)
plot(forecast.BVAR$forecast[,,2], probs=c(0.16,0.84),
main="P2I Forecast")
abline(h=0)
## End(Not run)