{"paper":{"title":"Generalized Estimating Equation for the Student-t Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","math.IT","math.PR","stat.TH"],"primary_cat":"math.ST","authors_text":"Atin Gayen, M. Ashok Kumar","submitted_at":"2018-01-27T15:04:48Z","abstract_excerpt":"In \\cite{KumarS15J2}, it was shown that a generalized maximum likelihood estimation problem on a (canonical) $\\alpha$-power-law model ($\\mathbb{M}^{(\\alpha)}$-family) can be solved by solving a system of linear equations. This was due to an orthogonality relationship between the $\\mathbb{M}^{(\\alpha)}$-family and a linear family with respect to the relative $\\alpha$-entropy (or the $\\mathscr{I}_\\alpha$-divergence). Relative $\\alpha$-entropy is a generalization of the usual relative entropy (or the Kullback-Leibler divergence). $\\mathbb{M}^{(\\alpha)}$-family is a generalization of the usual exp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.09100","kind":"arxiv","version":1},"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"}