bmgarch
Bayesian Multivariate GARCH Models
Fit Bayesian multivariate GARCH models using 'Stan' for full Bayesian inference. Generate (weighted) forecasts for means, variances (volatility) and correlations. Currently DCC(P,Q), CCC(P,Q), pdBEKK(P,Q), and BEKK(P,Q) parameterizations are implemented, based either on a multivariate gaussian normal or student-t distribution. DCC and CCC models are based on Engle (2002) doi:10.1198/073500102288618487 and Bollerslev (1990). The BEKK parameterization follows Engle and Kroner (1995) doi:10.1017/S0266466600009063 while the pdBEKK as well as the estimation approach for this package is described in Rast et al. (2020) doi:10.31234/osf.io/j57pk. The fitted models contain 'rstan' objects and can be examined with 'rstan' functions.
- Version2.0.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Engle (2002)
- Bollerslev (1990)
- Engle and Kroner (1995)
- Rast et al. (2020)
- Last release09/12/2023
Documentation
Team
Philippe Rast
MaintainerShow author detailsStephen Martin
Show author detailsRolesAuthor
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Last 30 days
This package has been downloaded 349 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 19 times.
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Last 365 days
This package has been downloaded 4,631 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jan 30, 2025 with 53 downloads.
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Dependencies
- Depends1 package
- Imports7 packages
- Suggests1 package
- Linking To6 packages