'Moreau-Yosida' Importance Sampling for Statistical Inference R package MYIS version 0.1.0 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). Software Depends: R (>= 4.1.0) Imports: stats, graphics Suggests: testthat (>= 3.0.0), knitr, rmarkdown Shikhar Tyagi <shikhar1093tyagi@gmail.com> Comprehensive R Archive Network (CRAN) Shikhar Tyagi [aut, cre] (ORCID: <https://orcid.org/0000-0003-1606-0844>), Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut] GPL-3 2026-08-05 application/tgz https://CRAN.R-project.org/package=MYIS doi:10.32614/CRAN.package.MYIS en-US