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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.
Package details |
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| Author | Darjus Hosszejni [aut, cre] (<https://orcid.org/0000-0002-3803-691X>), Gregor Kastner [aut] (<https://orcid.org/0000-0002-8237-8271>) |
| Maintainer | Darjus Hosszejni <darjus.hosszejni@icloud.com> |
| License | GPL (>= 2) |
| Version | 3.2.3 |
| URL | https://gregorkastner.github.io/stochvol/ |
| Package repository | View on CRAN |
| Installation |
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