Package: sanba
Type: Package
Title: Fitting Shared Atoms Nested Models via MCMC or Variational Bayes
Version: 0.0.3
Authors@R: c(
    person("Francesco", "Denti", ,"francescodenti.personal@gmail.com", 
    role = c("aut", "cre", "cph"),
    comment = c(ORCID = "0000-0001-5034-7414")),
    person("Laura", "D'Angelo", ,"laura.dangelo@live.com", 
    role = c("aut"),
    comment = c(ORCID = "0000-0003-2978-4702"))
  )
Maintainer: Francesco Denti <francescodenti.personal@gmail.com>
URL: https://github.com/fradenti/sanba
BugReports: https://github.com/fradenti/sanba/issues
Description: 
    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>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: Rcpp, matrixStats, salso, scales, RColorBrewer
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Language: en-US
Suggests: spelling
NeedsCompilation: yes
Packaged: 2025-09-24 18:21:38 UTC; fradenti
Author: Francesco Denti [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0001-5034-7414>),
  Laura D'Angelo [aut] (ORCID: <https://orcid.org/0000-0003-2978-4702>)
Repository: CRAN
Date/Publication: 2025-09-24 18:40:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2025-09-24 20:38:44 UTC; unix
Archs: sanba.so.dSYM
