SANple
0.2.0Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo
Overview
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.
Install
Health
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-0913 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Repository
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 4.0 median / 25 max
- Documented parameters
- 66%
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
38 5 exported
Complexity
7.7 avg / 25 max
Call network
38 nodes / 27 edges
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.2.0Latest
- RR 4.5.0 released · 2025-04-11
- 0.1.12024-06-02 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 0.1.02023-10-10
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-10-10
- Total releases
- 3 / 3 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 332 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet