Proximal Hamiltonian Monte Carlo for Non-Smooth Bayesian Inference
Overview
Implements the Proximal Hamiltonian Monte Carlo (p-HMC) algorithm for Bayesian sampling and estimation from non-differentiable target densities. The method decomposes a target potential into a smooth component f(x) and a non-smooth convex component g(x), approximating only g(x) via its Moreau-Yosida envelope while retaining exact gradient information for f(x). This approach, based on the methodology described in Shukla, Vats, and Chi (2025) doi:10.48550/arXiv.2510.22252, yields improved Hamiltonian conservation over full-potential smoothing approaches. The package provides generalized routines accepting user-defined probability density functions, log-likelihoods, priors, and proximal operators, together with automated hyperparameter tuning for the Moreau-Yosida regularization parameter, Markov chain Monte Carlo convergence diagnostics, effective sample size computation, and model evaluation metrics including the Akaike information criterion and Bayesian information criterion.
Install
Health
- OK13 OKNow
- OK7 OK2026-08-22
Documentation
- Help pages
- 5
- Examples that run
- 0%1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 25%
- Documented parameters
- 97%
- Return-value docs
- 100%
- Help pages citing references
- 80%
Downloads
Dependencies
Installing pHMC adds no packages beyond those that come with R.
Code & Tests
People & History
- 0.1.0Latest2026-08-21 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-08-21
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Download size
- 14 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("pHMC")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.