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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), and hybrid finite-infinite models. 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, Denti (2024) <doi:10.1214/24-BA1458>.

Versions across snapshots

VersionRepositoryFileSize
0.2.0 rolling linux/jammy R-4.5 SANple_0.2.0.tar.gz 504.5 KiB
0.2.0 rolling linux/noble R-4.5 SANple_0.2.0.tar.gz 508.0 KiB
0.2.0 rolling source/ R- SANple_0.2.0.tar.gz 332.9 KiB
0.2.0 latest linux/jammy R-4.5 SANple_0.2.0.tar.gz 504.5 KiB
0.2.0 latest linux/noble R-4.5 SANple_0.2.0.tar.gz 508.0 KiB
0.2.0 latest source/ R- SANple_0.2.0.tar.gz 332.9 KiB
0.2.0 2026-04-26 source/ R- SANple_0.2.0.tar.gz 332.9 KiB
0.2.0 2026-04-23 source/ R- SANple_0.2.0.tar.gz 332.9 KiB
0.2.0 2026-04-09 windows/windows R-4.5 SANple_0.2.0.zip 909.1 KiB
0.1.1 2025-04-20 source/ R- SANple_0.1.1.tar.gz 134.2 KiB

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