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stochvol (version 1.3.3)
Efficient Bayesian Inference for Stochastic Volatility (SV) Models
Description
Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models via Markov chain Monte Carlo (MCMC) methods.
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Install
install.packages('stochvol')
Monthly Downloads
1,769
Version
1.3.3
License
GPL (>= 2)
Maintainer
Gregor Kastner
Last Published
September 19th, 2017
Functions in stochvol (1.3.3)
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plot.svdraws
Graphical Summary of the Posterior Distribution
arpredict
Dynamic prediction for the AR-SV model
svsample
Markov Chain Monte Carlo (MCMC) Sampling for the Stochastic Volatility (SV) Model
paradensplot
Probability Density Function Plot for the Parameter Posteriors
logret
Computes (de-meaned) log returns.
exrates
Euro exchange rate data
paratraceplot
Trace Plot of MCMC Draws from the Parameter Posteriors
svsim
Simulating a Stochastic Volatility Process
svsample2
Minimal overhead version of
svsample
.
volplot
Plotting Quantiles of the Latent Volatilities
stochvol-package
Efficient Bayesian Inference for Stochastic Volatility (SV) Models
Extractors
Common Extractors for 'svdraws' Objects
predict.svdraws
Prediction of Future Log-Volatilities
updatesummary
Updating the Summary of MCMC Draws