Package: MYIS Type: Package Title: 'Moreau-Yosida' Importance Sampling for Statistical Inference Version: 0.1.0 Authors@R: c( person("Shikhar", "Tyagi", email = "shikhar1093tyagi@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1606-0844")), person("Arvind", "Pandey", email = "arvindmzu@gmail.com", role = "aut"), person("Bhupendra", "Singh", email = "bhupendra.rana@gmail.com", role = "aut"), person("Vrijesh", "Tripathi", email = "vrijesh.tripathi@uwi.edu", role = "aut")) Description: 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) , 'Pereyra' (2016) , 'Durmus' and others (2022) , 'Chen' and 'Shao' (1999) , 'Roberts' and 'Rosenthal' (1998) , 'Geweke' (1989) , 'Hesterberg' (1995) , and 'Balakrishnan' and 'Aggarwala' (2000, ISBN:978-0-8176-4001-9). License: GPL-3 Encoding: UTF-8 Language: en-US Depends: R (>= 4.1.0) Imports: stats, graphics Suggests: testthat (>= 3.0.0), knitr, rmarkdown Config/testthat/edition: 3 RoxygenNote: 7.3.3 VignetteBuilder: knitr NeedsCompilation: no Packaged: 2026-10-05 10:56:09 UTC; root Author: Shikhar Tyagi [aut, cre] (ORCID: ), Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut] Maintainer: Shikhar Tyagi Repository: https://shikhartyagi.r-universe.dev Date/Publication: 2026-08-05 07:50:12 UTC RemoteUrl: https://github.com/cran/MYIS RemoteRef: HEAD RemoteSha: ab601594a1f667f52ead773993fbd5fe19a1e02d