{"paper":{"title":"A cautionary tale on the efficiency of some adaptive Monte Carlo schemes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR","math.ST","stat.ME","stat.TH"],"primary_cat":"stat.CO","authors_text":"Yves F. Atchad\\'e","submitted_at":"2009-01-10T14:16:39Z","abstract_excerpt":"There is a growing interest in the literature for adaptive Markov chain Monte Carlo methods based on sequences of random transition kernels $\\{P_n\\}$ where the kernel $P_n$ is allowed to have an invariant distribution $\\pi_n$ not necessarily equal to the distribution of interest $\\pi$ (target distribution). These algorithms are designed such that as $n\\to\\infty$, $P_n$ converges to $P$, a kernel that has the correct invariant distribution $\\pi$. Typically, $P$ is a kernel with good convergence properties, but one that cannot be directly implemented. It is then expected that the algorithm will "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0901.1378","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"}