A new bivariate Poisson common shock model covering all possible degrees of dependence

DOI10.1016/j.spl.2018.04.013zbMath1392.60019OpenAlexW2799447825WikidataQ129880751 ScholiaQ129880751MaRDI QIDQ1644209

Juliana Schulz, Christian Genest, M'hamed Mesfioui

Publication date: 21 June 2018

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2018.04.013

zbMATH Keywords

correlationcomonotonicitypositive quadrant dependencecounter-monotonicitybivariate count datacommon shock variable

Mathematics Subject Classification ID

Point estimation (62F10) Exact distribution theory in statistics (62E15) Probability distributions: general theory (60E05)

Related Items (5)

Copula-based bivariate finite mixture regression models with an application for insurance claim count data ⋮ A multivariate Poisson model based on comonotonic shocks ⋮ Integral transformation of a copula function ⋮ Partially Schur-constant models ⋮ Testing independence between discrete random variables

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• Modeling and Generating Dependent Risk Processes for IRM and DFA
• A Primer on Copulas for Count Data
• Some Concepts of Dependence

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