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SANvi: Fitting Shared Atoms Nested Models via Variational Bayes

An efficient tool for fitting the nested common and shared atoms models using variational Bayes approximate inference for fast computation. 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 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>.

Version: 0.1.0
Depends: scales, RColorBrewer
Imports: Rcpp, matrixStats
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-10-10
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/SANvi/issues
License: MIT + file LICENSE
URL: https://github.com/fradenti/SANvi
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: SANvi results

Documentation:

Reference manual: SANvi.pdf

Downloads:

Package source: SANvi_0.1.0.tar.gz
Windows binaries: r-devel: SANvi_0.1.0.zip, r-release: SANvi_0.1.0.zip, r-oldrel: SANvi_0.1.0.zip
macOS binaries: r-release (arm64): SANvi_0.1.0.tgz, r-oldrel (arm64): SANvi_0.1.0.tgz, r-release (x86_64): SANvi_0.1.0.tgz, r-oldrel (x86_64): SANvi_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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