Statistical Inference for a New Class of Multivariate Pareto Distributions

DOI10.1080/03610918.2013.861627zbMath1341.62113OpenAlexW3121608190MaRDI QIDQ2809618

Raluca Vernic, Alexandru V. Asimit, Edward Furman

Publication date: 30 May 2016

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://openaccess.city.ac.uk/id/eprint/13123/1/Asimit%20et%20al%202013_rev3.pdf

zbMATH Keywords

maximum likelihood estimationmethod of momentsexpectation-maximization algorithmcommon shock modelmultivariate Pareto distribution

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Point estimation (62F10) Probability distributions: general theory (60E05)

Related Items (9)

Inference about the bivariate new extended Weibull distribution based on complete and censored data ⋮ Inference for the tail conditional allocation: large sample properties, insurance risk assessment, and compound sums of concomitants ⋮ A Marshall-Olkin type multivariate model with underlying dependent shocks ⋮ Tail maximal dependence in bivariate models: estimation and applications ⋮ Archimedean-based Marshall-Olkin distributions and related dependence structures ⋮ JOINT LIFE INSURANCE PRICING USING EXTENDED MARSHALL–OLKIN MODELS ⋮ A Reconciliation of the Top-Down and Bottom-Up Approaches to Risk Capital Allocations: Proportional Allocations Revisited ⋮ Weighted allocations, their concomitant-based estimators, and asymptotics ⋮ Some variations of EM algorithms for Marshall-Olkin bivariate Pareto distribution with location and scale

Cites Work

• Unnamed Item
• On a multivariate Pareto distribution
• Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm
• On the convergence properties of the EM algorithm
• ML estimation for multivariate shock models via an EM algorithm

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