{"paper":{"title":"Hankel determinants of random moment sequences","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Dominik Tomecki, Holger Dette","submitted_at":"2015-08-03T23:25:20Z","abstract_excerpt":"For $ t \\in [0,1]$ let $\\underline{H}_{2\\lfloor nt \\rfloor} = ( m_{i+j})_{i,j=0}^{\\lfloor nt \\rfloor} $ denote the Hankel matrix of order $2\\lfloor nt \\rfloor$ of a random vector $(m_1,\\ldots ,m_{2n})$ on the moment space $\\mathcal{M}_{2n}(I)$ of all moments (up to the order $2n$) of probability measures on the interval $I \\subset \\mathbb{R} $. In this paper we study the asymptotic properties of the stochastic process $\\{ \\log \\det \\underline{H}_{2\\lfloor nt \\rfloor} \\}_{t\\in [0,1]}$ as $n \\to \\infty$. In particular weak convergence and corresponding large deviation principles are derived afte"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.00617","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":""},"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"}