# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "sanba" in publications use:' type: software license: MIT title: 'sanba: Fitting Shared Atoms Nested Models via MCMC or Variational Bayes' version: 0.0.4 doi: 10.32614/CRAN.package.sanba abstract: '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, 2026). 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) , D’Angelo, Canale, Yu, Guindani (2023) , D’Angelo, Denti (2026) .' authors: - family-names: Denti given-names: Francesco email: francescodenti.personal@gmail.com orcid: https://orcid.org/0000-0001-5034-7414 - family-names: D'Angelo given-names: Laura email: laura.dangelo@live.com orcid: https://orcid.org/0000-0003-2978-4702 repository: https://cran.r-universe.dev repository-code: https://github.com/fradenti/sanba commit: 4cc88e2ef620ff8ec64131bd32a4a140be8f6482 url: https://github.com/fradenti/sanba date-released: '2026-06-15' contact: - family-names: Denti given-names: Francesco email: francescodenti.personal@gmail.com orcid: https://orcid.org/0000-0001-5034-7414