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)