doi:10.1016/j.csda.2013.01.002> and Hosszejni and Kastner (2019) <doi:10.1007/978-3-030-30611-3_8>; the most common use cases are described in Hosszejni and Kastner (2021) <doi:10.18637/jss.v100.i12> and Kastner (2016) <doi:10.18637/jss.v069.i05> and the package examples.">

stochvol: Efficient Bayesian Inference for Stochastic Volatility (SV) Models (original) (raw)

Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models with and without asymmetry (leverage) 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> and Hosszejni and Kastner (2019) <doi:10.1007/978-3-030-30611-3_8>; the most common use cases are described in Hosszejni and Kastner (2021) <doi:10.18637/jss.v100.i12> and Kastner (2016) <doi:10.18637/jss.v069.i05> and the package examples.

Version: 3.2.5
Depends: R (≥ 3.5)
Imports: Rcpp (≥ 1.0), coda (≥ 0.19), graphics, stats, utils, grDevices
LinkingTo: Rcpp, RcppArmadillo (≥ 0.9.900)
Suggests: testthat (≥ 2.3.2), mvtnorm, knitr
Published: 2024-10-28
DOI: 10.32614/CRAN.package.stochvol
Author: Darjus Hosszejni ORCID iD [aut, cre], Gregor Kastner ORCID iD [aut]
Maintainer: Darjus Hosszejni <darjus.hosszejni at icloud.com>
BugReports: https://github.com/gregorkastner/stochvol/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://gregorkastner.github.io/stochvol/
NeedsCompilation: yes
Citation: stochvol citation info
Materials: NEWS
In views: Bayesian, Finance, TimeSeries
CRAN checks: stochvol results

Documentation:

Downloads:

Reverse dependencies:

Reverse imports: bayesianVARs, BGVAR, bsvars, factorstochvol, shrinkDSM, shrinkTVP, shrinkTVPVAR
Reverse linking to: bayesianVARs, BGVAR, factorstochvol, shrinkDSM, shrinkTVP, shrinkTVPVAR
Reverse suggests: bsreg, tensorBSS, tsBSS

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