stochvol (version 3.2.4)

plot.svpredict: Graphical Summary of the Posterior Predictive Distribution

Description

plot.svpredict and plot.svlpredict generate some plots visualizing the posterior predictive distribution of future volatilites and future observations.

Usage

# S3 method for svpredict
plot(x, quantiles = c(0.05, 0.25, 0.5, 0.75, 0.95), ...)

Value

Called for its side effects. Returns argument x invisibly.

Arguments

x

svpredict or svlpredict object.

quantiles

Which quantiles to plot? Defaults to c(.05, .25, .5, .75, .95).

...

further arguments are passed on to the invoked ts.plot or boxplot function.

See Also

Other plotting: paradensplot(), paratraceplot.svdraws(), paratraceplot(), plot.svdraws(), volplot()

Other plotting: paradensplot(), paratraceplot.svdraws(), paratraceplot(), plot.svdraws(), volplot()

Examples

## Simulate a short and highly persistent SV process
sim <- svsim(100, mu = -10, phi = 0.99, sigma = 0.1)

## Obtain 5000 draws from the sampler (that's not a lot)
draws <- svsample(sim$y, draws = 5000, burnin = 1000)

## Predict 10 steps ahead
pred <- predict(draws, 10)

## Visualize the predicted distributions
plot(pred)

## Plot the latent volatilities and some forecasts
plot(draws, forecast = pred)