fipp
Induced Priors in Bayesian Mixture Models
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.
- Version1.0.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- Last release02/11/2021
Documentation
Team
Jan Greve
Bettina Grün
Gertraud Malsiner-Walli
Sylvia Frühwirth-Schnatter
Insights
Last 30 days
This package has been downloaded 158 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 10 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,298 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 Jul 21, 2024 with 147 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Suggests2 packages
- Linking To2 packages