SANple

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.

Last 30 days

This package has been downloaded 400 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 5,357 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Sep 11, 2024 with 60 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.