Package: bmgarch 2.0.0.9000

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.

Authors:Philippe Rast [aut, cre], Stephen Martin [aut]

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Bug tracker:https://github.com/ph-rast/bmgarch/issues

On CRAN:

5 exports 16 stars 2.07 score 70 dependencies 5 scripts 410 downloads

Last updated 1 years agofrom:a7d8e1c3d5. Checks:OK: 1 NOTE: 8. Indexed: yes.

Exports:bmgarchbmgarch_listforecastloomodel_weights

Dependencies:abindbackportsBHcallrcheckmateclicolorspacecurldescdistributionalfansifarverforecastfracdiffgenericsggplot2gluegridExtragtableinlineisobandjsonlitelabelinglatticelifecyclelmtestloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmennetnumDerivpillarpkgbuildpkgconfigposteriorprocessxpsquadprogquantmodQuickJSRR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackrlangrstanrstantoolsscalesStanHeaderstensorAtibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo