doi:10.1080/01621459.2021.1933499>, D’Angelo, Denti (2024) <doi:10.1214/24-BA1458>.">

SANple: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo (original) (raw)

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) <doi:10.1080/01621459.2021.1933499>, D’Angelo, Denti (2024) <doi:10.1214/24-BA1458>.

Version: 0.2.0
Depends: scales, RColorBrewer
Imports: Rcpp, salso
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Published: 2025-09-24
DOI: 10.32614/CRAN.package.SANple
Author: Francesco Denti ORCID iD [aut, cre], Laura D'Angelo ORCID iD [aut, cph]
Maintainer: Francesco Denti <francescodenti.personal at gmail.com>
BugReports: https://github.com/laura-dangelo/SANple/issues
License: MIT + file
URL: https://github.com/laura-dangelo/SANple
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: SANple results

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