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  "Title": "Importance Sampling Inference for Censored Univariate Data",
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  "Description": "Distribution-independent framework for importance-sampling\ninference with univariate observations subject to censoring or\ntruncation. Users provide probability functions and a proposal\nover model parameters. Constructs observed-data likelihood\ncontributions, computes numerically stable importance weights,\nand supplies posterior, likelihood, predictive, diagnostic, and\nmodel-comparison summaries. Covers complete, right, left,\ninterval, Type-I, Type-II, progressive Type-II, first-failure,\nprogressive first-failure, doubly Type-II, middle-censored, and\nleft/right-truncated data. Methods for importance sampling and\ncensoring schemes are described in Geweke (1989)\n<doi:10.2307/2290062>, Hesterberg (1995)\n<doi:10.1080/00031305.1995.10476138>, Robert and Casella (2004,\nISBN:978-0-387-21617-1), Kundu and Joarder (2006)\n<doi:10.1016/j.csda.2005.05.002>, Banerjee and Kundu (2008)\n<doi:10.1109/TR.2008.916890>, Iyer, Jammalamadaka, and Kundu\n(2008) <doi:10.1016/j.jspi.2007.03.062>, Wu and Kus (2009)\n<doi:10.1016/j.csda.2009.03.010>, Prajapati, Mitra, and Kundu\n(2019) <doi:10.1007/s13571-018-0167-0>, Mondal and Kundu (2020)\n<doi:10.1080/03610926.2018.1554128>, Balakrishnan and Aggarwala\n(2000, ISBN:980-1-4612-1334-5), Ding and Gui (2023)\n<doi:10.3390/math11092003>, Nagar, Kumar, and Krishna (2026)\n<doi:10.59467/IJASS.2026.22.1>, Goel and Krishna (2026)\n<doi:10.1007/s13198-026-03208-w>, Yadav, Jaiswal, and Yadav\n(2026) <doi:10.1007/s11135-026-02647-8>, and Goel, Kumar, and\nKrishna (2026, \"Estimation in power Lindley distributions using\nbalanced joint progressively Type-II censored data\").",
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