MYIS: 'Moreau-Yosida' Importance Sampling for Statistical Inference
Implements 'Moreau-Yosida' Markov chain Monte Carlo ('MCMC')
importance sampling for parameter estimation and Bayesian inference under
smooth, non-differentiable, or light-tailed target posterior distributions
and arbitrary probability models with complete or censored data. Users supply
user-defined probability density functions, optional distribution functions,
parameter ranges, and observations subject to complete, right, left, interval,
Type-I, Type-II, progressive Type-II, first-failure, or truncation schemes.
Constructs 'Moreau-Yosida' envelopes, gradient-based proposals ('MALA',
'HMC', or 'RWM'), self-normalized importance weights, batch-means asymptotic
variance estimates, and Bayesian marginal quantiles. Methodologies are based
on 'Shukla', 'Vats', and 'Chi' (2025) <doi:10.48550/arXiv.2501.02228>,
'Pereyra' (2016) <doi:10.1111/sjos.12208>, 'Durmus' and others (2022)
<doi:10.1214/22-EJS2027>, 'Chen' and 'Shao' (1999) <doi:10.1214/ss/1009211804>,
'Roberts' and 'Rosenthal' (1998) <doi:10.1214/aoap/1028903378>, 'Geweke' (1989)
<doi:10.2307/2290062>, 'Hesterberg' (1995) <doi:10.1080/00031305.1995.10476138>,
and 'Balakrishnan' and 'Aggarwala' (2000, ISBN:978-0-8176-4001-9).
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
stats, graphics |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-08-05 |
| DOI: |
10.32614/CRAN.package.MYIS |
| Author: |
Shikhar Tyagi 
[aut, cre],
Arvind Pandey [aut],
Bhupendra Singh [aut],
Vrijesh Tripathi [aut] |
| Maintainer: |
Shikhar Tyagi <shikhar1093tyagi at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Language: |
en-US |
| CRAN checks: |
MYIS results |
Documentation:
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