Package: fipp 1.0.0
Jan Greve
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) <arxiv:2005.09918>). For methodological details, please refer to Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2020) <arxiv:2012.12337>) as well as the package vignette.
Authors:
fipp_1.0.0.tar.gz
fipp_1.0.0.tar.gz(r-4.5-noble)fipp_1.0.0.tar.gz(r-4.4-noble)
fipp_1.0.0.tgz(r-4.4-emscripten)fipp_1.0.0.tgz(r-4.3-emscripten)
fipp.pdf |fipp.html✨
fipp/json (API)
NEWS
| # Install 'fipp' in R: |
| install.packages('fipp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:9ffda952f8. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 31 2024 |
Dependencies:matrixStatsRcppRcppArmadillo
