Estimate Bayesian nested mixture models via Markov Chain Monte Carlo methods. Specifically, the package implements the common atoms model (Denti et al., 2023), and hybrid finite-infinite models. All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyzing the results of the fitting procedure. References: Denti, Camerlenghi, Guindani, Mira (2023) tools:::Rd_expr_doi("10.1080/01621459.2021.1933499"), D’Angelo, Denti (2024) tools:::Rd_expr_doi("10.1214/24-BA1458").
Maintainer: Francesco Denti francescodenti.personal@gmail.com (ORCID)
Authors:
Laura D'Angelo laura.dangelo@live.com (ORCID) [copyright holder]
Useful links: