Induced Priors in Bayesian Mixture Models R package fipp version 1.0.1 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 (2021) <doi:10.1214/21-ba1294>). For methodological details, please refer to Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2022) <doi:10.1111/anzs.12350>) as well as the package vignette. Software Depends: R (>= 3.5.0) Imports: Rcpp, stats, matrixStats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Jan Greve <jangre@uio.no> Comprehensive R Archive Network (CRAN) Jan Greve [aut, cre], Bettina Grün [ctb] (ORCID: <https://orcid.org/0000-0001-7265-4773>), Gertraud Malsiner-Walli [ctb] (ORCID: <https://orcid.org/0000-0002-1213-4749>), Sylvia Frühwirth-Schnatter [ctb] (ORCID: <https://orcid.org/0000-0003-0516-5552>) GPL-2 2026-08-04 application/tgz https://CRAN.R-project.org/package=fipp doi:10.32614/CRAN.package.fipp