fipp: Induced Priors in Bayesian Mixture Models (original) (raw)
Computes implicitly induced quantities from prior/hyperparameter specifications of three Mixtures of Finite Mixtures models: Dirichlet Process Mixtures (DPMs; Escobar and West (1995) <doi:10.1080/01621459.1995.10476550>), Static Mixtures of Finite Mixtures (Static MFMs; Miller and Harrison (2018) <doi:10.1080/01621459.2016.1255636>), and Dynamic Mixtures of Finite Mixtures (Dynamic MFMs; Frühwirth-Schnatter, Malsiner-Walli and Grün (2020) <doi:10.48550/arXiv.2005.09918>). For methodological details, please refer to Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2020) <doi:10.48550/arXiv.2012.12337>) as well as the package vignette.
Version: | 1.0.0 |
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Depends: | R (≥ 3.5.0) |
Imports: | Rcpp, stats, matrixStats |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | knitr, rmarkdown |
Published: | 2021-02-11 |
DOI: | 10.32614/CRAN.package.fipp |
Author: | Jan Greve [aut, cre], Bettina Grün |
Maintainer: | Jan Greve <jan.greve at wu.ac.at> |
License: | GPL-2 |
NeedsCompilation: | yes |
Materials: | README, NEWS |
CRAN checks: | fipp results [issues need fixing before 2025-11-15] |
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