plot.svlpredict generate some plots
visualizing the posterior predictive distribution of future volatilites and
Which quantiles to plot? Defaults to
further arguments are passed on to the invoked
Called for its side effects. Returns argument
svlpredict objects can also be
plot.svdraws for a possibly more useful
visualization. See the examples in
those below for use cases.
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## 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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