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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: | 3.2.4 |
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: | 2024-03-03 |
DOI: | 10.32614/CRAN.package.stochvol |
Author: | Darjus Hosszejni |
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 |
Package source: | stochvol_3.2.4.tar.gz |
Windows binaries: | r-devel: stochvol_3.2.4.zip, r-release: stochvol_3.2.4.zip, r-oldrel: stochvol_3.2.4.zip |
macOS binaries: | r-release (arm64): stochvol_3.2.4.tgz, r-oldrel (arm64): stochvol_3.2.4.tgz, r-release (x86_64): stochvol_3.2.4.tgz, r-oldrel (x86_64): stochvol_3.2.4.tgz |
Old sources: | stochvol archive |
Reverse imports: | bayesianVARs, BGVAR, bsvars, factorstochvol, shrinkDSM, shrinkTVP |
Reverse linking to: | bayesianVARs, BGVAR, factorstochvol, shrinkDSM, shrinkTVP |
Reverse suggests: | bsreg, stochvolTMB, tensorBSS, tsBSS |
Please use the canonical form https://CRAN.R-project.org/package=stochvol to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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