SANple: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo

Estimate Bayesian nested mixture models via Markov Chain Monte Carlo methods. Specifically, the package implements the common atoms model (Denti et al., 2023), its finite version (D'Angelo et al., 2023), and a hybrid finite-infinite model. 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, Canale, Yu, Guindani (2023) <doi:10.1111/biom.13626>.

Version: 0.1.0
Depends: scales, RColorBrewer
Imports: Rcpp, salso
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Published: 2023-10-10
Author: Laura D'Angelo ORCID iD [aut, cre, cph], Francesco Denti ORCID iD [aut]
Maintainer: Laura D'Angelo <laura.dangelo at live.com>
BugReports: https://github.com/laura-dangelo/SANple/issues
License: MIT + file LICENSE
URL: https://github.com/laura-dangelo/SANple
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: SANple results

Documentation:

Reference manual: SANple.pdf

Downloads:

Package source: SANple_0.1.0.tar.gz
Windows binaries: r-prerel: SANple_0.1.0.zip, r-release: SANple_0.1.0.zip, r-oldrel: SANple_0.1.0.zip
macOS binaries: r-prerel (arm64): SANple_0.1.0.tgz, r-release (arm64): SANple_0.1.0.tgz, r-oldrel (arm64): SANple_0.1.0.tgz, r-prerel (x86_64): SANple_0.1.0.tgz, r-release (x86_64): SANple_0.1.0.tgz

Linking:

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