gregorkastner/stochvol: Efficient Bayesian Inference for Stochastic Volatility (SV) Models

Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models via Markov chain Monte Carlo (MCMC) methods. Methodological details are given in Kastner and Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002>; the most common use cases are described in Kastner (2016) <doi:10.18637/jss.v069.i05>. Also incorporates SV with leverage.

Getting started

Package details

Maintainer
LicenseGPL (>= 2)
Version2.0.5
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("gregorkastner/stochvol")
gregorkastner/stochvol documentation built on Sept. 3, 2019, 1:58 p.m.