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: 0.0.1
Depends: scales, RColorBrewer
Imports: Rcpp, matrixStats, salso
LinkingTo: cpp11, Rcpp, RcppArmadillo, RcppProgress
Published: 2025-05-23
DOI: 10.32614/CRAN.package.sanba
Author: Francesco Denti ORCID iD [aut, cre, cph], Laura D'Angelo ORCID iD [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:

Reference manual: sanba.pdf

Downloads:

Package source: sanba_0.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): sanba_0.0.1.tgz, r-oldrel (arm64): sanba_0.0.1.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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