| plot.svpredict {stochvol} | R Documentation |
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 class 'svpredict'
plot(x, quantiles = c(0.05, 0.25, 0.5, 0.75, 0.95), ...)
Arguments
x |
|
quantiles |
Which quantiles to plot? Defaults to
|
... |
further arguments are passed on to the invoked
|
Value
Called for its side effects. Returns argument x invisibly.
Note
Note that svpredict or svlpredict objects can also be
used within plot.svdraws for a possibly more useful
visualization. See the examples in predict.svdraws and
those below for use cases.
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)