{"paper":{"title":"Controlled Accuracy Gibbs Sampling of Order Constrained Non-IID Ordered Random Variates","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Caleb Miller, Jem N. Corcoran","submitted_at":"2020-12-31T05:11:22Z","abstract_excerpt":"Order statistics arising from $m$ independent but not identically distributed random variables are typically constructed by arranging some $X_{1}, X_{2}, \\ldots, X_{m}$, with $X_{i}$ having distribution function $F_{i}(x)$, in increasing order denoted as $X_{(1)} \\leq X_{(2)} \\leq \\ldots \\leq X_{(m)}$. In this case, $X_{(i)}$ is not necessarily associated with $F_{i}(x)$. Assuming one can simulate values from each distribution, one can generate such \"non-iid\" order statistics by simulating $X_{i}$ from $F_{i}$, for $i=1,2,\\ldots, m$, and arranging them in order. In this paper, we consider the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.15452","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2012.15452/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}