Graphical Summary of the Posterior Predictive Distribution
plot.svpredict and plot.svlpredict generate some plots
visualizing the posterior predictive distribution of future volatilites and
future observations.
## S3 method for class 'svpredict' plot(x, quantiles = c(0.05, 0.25, 0.5, 0.75, 0.95), ...)
Called for its side effects. Returns argument x invisibly.
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.
Other plotting:
paradensplot(),
paratraceplot.svdraws(),
paratraceplot(),
plot.svdraws(),
volplot()
Other plotting:
paradensplot(),
paratraceplot.svdraws(),
paratraceplot(),
plot.svdraws(),
volplot()
## 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)
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