{"paper":{"title":"Tail dependence convergence rate for the bivariate skew normal under the equal-skewness condition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Eugene Seneta, Thomas Fung","submitted_at":"2015-02-21T00:30:56Z","abstract_excerpt":"We derive the rate of decay of the tail dependence of the bivariate skew normal distribution under the equal-skewness condition {\\theta}1 = {\\theta}2,= {\\theta}, say. The rate of convergence depends on whether {\\theta} > 0 or {\\theta} < 0. The latter case gives rate asymp- totically identical with the case {\\theta} = 0. The asymptotic behaviour of the quantile function for the univariate skew normal is part of the theoretical development."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1502.06046","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"}