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stochvol
View on CRAN: Click
here
Download and install stochvol package within the R console
Install from CRAN:
install.packages("stochvol")
Install from Github:
library("remotes")
install_github("cran/stochvol")
Install by package version:
library("remotes")
install_version("stochvol", "3.2.5")
Attach the package and use:
library("stochvol")
Maintained by
Darjus Hosszejni
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.stochvol . https://github.com/gregorkastner/stochvol/issues . https://gregorkastner.github.io/stochvol/ . stochvol citation info . stochvol results . stochvol.pdf . Dealing with Stochastic Volatility in Time Series Using the R Package stochvol . Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol . stochvol_3.2.5.tar.gz . stochvol_3.2.5.zip . stochvol_3.2.5.zip . stochvol_3.2.5.zip . stochvol_3.2.5.tgz . stochvol_3.2.5.tgz . stochvol_3.2.5.tgz . stochvol_3.2.5.tgz . stochvol_3.2.5.tgz . stochvol_3.2.5.tgz . stochvol archive . factorstochvol . factorstochvol . stochvolTMB . https://CRAN.R-project.org/package=stochvol .
First Published: 2013-01-23
Latest Update: 2024-03-03
Description:
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.
How to cite:
Darjus Hosszejni (2013). stochvol: Efficient Bayesian Inference for Stochastic Volatility (SV) Models. R package version 3.2.5, https://cran.r-project.org/web/packages/stochvol. Accessed 31 Mar. 2025.
Previous versions and publish date:
0.5-0 (2013-01-23 16:29), 0.5-1 (2013-01-28 15:46), 0.6-0 (2013-04-17 19:22), 0.6-1 (2013-07-09 14:57), 0.7-0 (2013-10-10 00:26), 0.7-1 (2013-10-22 00:57), 0.8-0 (2014-02-06 20:02), 0.8-1 (2014-02-07 00:32), 0.8-2 (2014-05-16 07:39), 0.8-4 (2014-07-01 14:52), 0.9-0 (2014-10-16 23:02), 0.9-1 (2014-12-27 23:38), 1.0.0 (2015-01-28 16:00), 1.1.0 (2015-05-15 22:02), 1.1.1 (2015-05-23 02:03), 1.1.2 (2015-06-29 19:25), 1.1.3 (2015-06-30 08:42), 1.2.0 (2015-07-15 23:48), 1.2.1 (2015-11-27 08:53), 1.2.2 (2016-01-01 22:14), 1.2.3 (2016-02-18 08:56), 1.3.0 (2016-08-24 22:08), 1.3.1 (2016-10-19 00:39), 1.3.2 (2016-10-26 14:28), 1.3.3 (2017-09-19 02:32), 2.0.0 (2019-02-01 09:40), 2.0.1 (2019-02-26 23:10), 2.0.2 (2019-03-27 21:20), 2.0.3 (2019-05-29 07:30), 2.0.4 (2019-06-26 12:30), 3.0.0 (2020-11-03 08:10), 3.0.1 (2020-11-04 17:30), 3.0.2 (2020-11-17 18:50), 3.0.3 (2020-11-24 16:30), 3.0.4 (2021-02-09 20:20), 3.0.5 (2021-05-16 16:20), 3.0.6 (2021-05-20 17:20), 3.1.0 (2021-07-12 17:20), 3.2.0 (2021-11-26 22:30), 3.2.1 (2023-03-10 13:50), 3.2.3 (2023-11-27 00:30), 3.2.4 (2024-03-03 13:10)
Other packages that cited stochvol R package
View stochvol citation profile
Other R packages that stochvol depends,
imports, suggests or enhances
Complete documentation for stochvol
Functions, R codes and Examples using
the stochvol R package
Some associated functions: expert_defaults . exrates . extractors . logret . paradensplot . paratraceplot . paratraceplot.svdraws . plot.svdraws . plot.svpredict . predict.svdraws . specify_priors . stochvol-package . sv_prior . svlm . svsample . svsample_cpp . svsample_roll . svsim . update_fast_sv . update_general_sv . update_regressors . update_t_error . updatesummary . validate_and_process_expert . volplot .
Some associated R codes: catch-routine-registration.R . exports.R . generics.R . plotting.R . simulation.R . stochvol-cpp-doc.R . stochvol-package.R . util.R . utilities_svdraws.R . validation.R . wrappers.R . zzz.R . Full stochvol package functions and examples
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