Package: stochvol 3.2.5
stochvol: Efficient Bayesian Inference for Stochastic Volatility (SV) Models
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.
Authors:
stochvol_3.2.5.tar.gz
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stochvol_3.2.5.tgz(r-4.4-x86_64)stochvol_3.2.5.tgz(r-4.4-arm64)stochvol_3.2.5.tgz(r-4.3-x86_64)stochvol_3.2.5.tgz(r-4.3-arm64)
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stochvol.pdf |stochvol.html✨
stochvol/json (API)
NEWS
# Install 'stochvol' in R: |
install.packages('stochvol', repos = c('https://gregorkastner.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gregorkastner/stochvol/issues
- exrates - Euro exchange rate data
Last updated 26 days agofrom:30c2e52000. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 28 2024 |
R-4.5-win-x86_64 | OK | Oct 28 2024 |
R-4.5-linux-x86_64 | OK | Oct 28 2024 |
R-4.4-win-x86_64 | OK | Oct 28 2024 |
R-4.4-mac-x86_64 | OK | Oct 28 2024 |
R-4.4-mac-aarch64 | OK | Oct 28 2024 |
R-4.3-win-x86_64 | OK | Oct 28 2024 |
R-4.3-mac-x86_64 | OK | Oct 28 2024 |
R-4.3-mac-aarch64 | OK | Oct 28 2024 |
Exports:default_fast_svget_default_fast_svget_default_general_svlatentlatent0logretparaparadensplotparatraceplotpredlatentpredvolapredypriorsruntimesampled_parametersspecify_priorssv_betasv_constantsv_exponentialsv_gammasv_infinitysv_inverse_gammasv_multinormalsv_normalsvbetasvlmsvlsamplesvlsample_rollsvsamplesvsample_fast_cppsvsample_general_cppsvsample_rollsvsample2svsimsvtausvtlsamplesvtlsample_rollsvtsamplesvtsample_rollthinningupdate_fast_svupdate_general_svupdate_regressorsupdate_t_errorupdatesummaryvalidate_and_process_expertvolavolplot
Dependencies:codalatticeRcppRcppArmadillo
Dealing with Stochastic Volatility in Time Series Using the R Package stochvol
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usingknitr::knitr
on Oct 28 2024.Last update: 2021-05-19
Started: 2018-01-10
Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
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usingknitr::knitr
on Oct 28 2024.Last update: 2021-11-29
Started: 2020-10-30