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  "Title": "'Moreau-Yosida' Importance Sampling for Statistical Inference",
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  "Description": "Implements 'Moreau-Yosida' Markov chain Monte Carlo\n('MCMC') importance sampling for parameter estimation and\nBayesian inference under smooth, non-differentiable, or\nlight-tailed target posterior distributions and arbitrary\nprobability models with complete or censored data. Users supply\nuser-defined probability density functions, optional\ndistribution functions, parameter ranges, and observations\nsubject to complete, right, left, interval, Type-I, Type-II,\nprogressive Type-II, first-failure, or truncation schemes.\nConstructs 'Moreau-Yosida' envelopes, gradient-based proposals\n('MALA', 'HMC', or 'RWM'), self-normalized importance weights,\nbatch-means asymptotic variance estimates, and Bayesian\nmarginal quantiles. Methodologies are based on 'Shukla',\n'Vats', and 'Chi' (2025) <doi:10.48550/arXiv.2501.02228>,\n'Pereyra' (2016) <doi:10.1111/sjos.12208>, 'Durmus' and others\n(2022) <doi:10.1214/22-EJS2027>, 'Chen' and 'Shao' (1999)\n<doi:10.1214/ss/1009211804>, 'Roberts' and 'Rosenthal' (1998)\n<doi:10.1214/aoap/1028903378>, 'Geweke' (1989)\n<doi:10.2307/2290062>, 'Hesterberg' (1995)\n<doi:10.1080/00031305.1995.10476138>, and 'Balakrishnan' and\n'Aggarwala' (2000, ISBN:978-0-8176-4001-9).",
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  "Maintainer": "Shikhar Tyagi <shikhar1093tyagi@gmail.com>",
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      "title": "Compute Importance Sampling Effective Sample Size",
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      "title": "Moreau-Yosida Envelope and Proximal Mapping Computation",
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      "title": "Moreau-Yosida MCMC Importance Sampling Estimator",
      "topics": [
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      "title": "Diagnostic Plots for Moreau-Yosida Importance Sampling",
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      "title": "Print Moreau-Yosida Importance Sampling Results",
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      "title": "Print Summary of Moreau-Yosida Importance Sampling Object",
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      "topics": [
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      "title": "Metropolis-Adjusted Langevin Algorithm targeting Moreau-Yosida Density",
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      "title": "Summary of Moreau-Yosida Importance Sampling Object",
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