sanba: Fitting Shared Atoms Nested Models via MCMC or Variational Bayes
An efficient tool for fitting nested mixture models based on a shared set of
atoms via Markov Chain Monte Carlo and variational inference algorithms.
Specifically, the package implements the common atoms model (Denti et al., 2023),
its finite version (similar to D'Angelo et al., 2023), and a hybrid finite-infinite
model (D'Angelo and Denti, 2024). All models implement univariate nested mixtures
with Gaussian kernels equipped with a normal-inverse gamma prior distribution
on the parameters. Additional functions are provided to help analyze the
results of the fitting procedure.
References:
Denti, Camerlenghi, Guindani, Mira (2023) <doi:10.1080/01621459.2021.1933499>,
D’Angelo, Canale, Yu, Guindani (2023) <doi:10.1111/biom.13626>,
D’Angelo, Denti (2024) <doi:10.1214/24-BA1458>.
| Version: |
0.0.3 |
| Imports: |
Rcpp, matrixStats, salso, scales, RColorBrewer |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppProgress |
| Suggests: |
spelling |
| Published: |
2025-09-24 |
| DOI: |
10.32614/CRAN.package.sanba |
| Author: |
Francesco Denti 
[aut, cre, cph],
Laura D'Angelo
[aut] |
| Maintainer: |
Francesco Denti <francescodenti.personal at gmail.com> |
| BugReports: |
https://github.com/fradenti/sanba/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/fradenti/sanba |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Materials: |
README, NEWS |
| CRAN checks: |
sanba results |
Documentation:
Downloads:
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