{"paper":{"title":"Insurance Applications of Some New Dependence Models derived from Multivariate Collective Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR"],"primary_cat":"stat.AP","authors_text":"Enkelejd Hashorva, Gildas Ratovomirija, Maissa Tamraz","submitted_at":"2016-03-06T20:36:27Z","abstract_excerpt":"Consider two different portfolios which have claims triggered by the same events. Their corresponding collective model over a fixed time period is given in terms of individual claim sizes $(X_i,Y_i), i\\ge 1$ and a claim counting random variable $N$. In this paper we are concerned with the joint distribution function $F$ of the \\ece{largest claim sizes} $(X_{N:N}, Y_{N:N})$. By allowing $N$ to depend on some parameter, say $\\theta$, then $F=F(\\theta)$ is for various choices of $N$ a tractable parametric family of bivariate distribution functions. We present three applications of the implied par"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.01871","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"}