Multivariate Count Data Generalized Linear Models: Three Approaches Based on the Sarmanov Distribution-Reference-Cited by-同舟云学术

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Multivariate Count Data Generalized Linear Models: Three Approaches Based on the Sarmanov Distribution

Published:2017 Issue: Volume: Page:
ISSN:1556-5068
Container-title:SSRN Electronic Journal
language:en
Short-container-title:SSRN Journal

Author:

Bolancc Catalina,Vernic Raluca

Publisher

Elsevier BV

Reference22 articles.

1. Sarmanov family of multivariate distributions for bivariate dynamic claim counts model;A Abdallah;Insurance: Mathematics and Economics,2016

2. On the bivariate distribution and copula. an application on insurance data using truncated marginal distributions;Z Bahraoui;Statistics and Operations Research Transactions, SORT,2015

3. Testing extreme value copulas to estimate the quantile;Z Bahraoui;Statistics and Operations Research Transactions,2014

4. Bayesian multivariate poisson models for insurance ratemaking;L Bermudez;Insurance: Mathematics and Economics,2011

5. Quantifying the risk using copulae with nonparametric marginal;C Bolanc�;Insurance: Mathematics and Economics,2014

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On the evaluation of some multivariate compound distributions with Sarmanov’s counting distribution;Insurance: Mathematics and Economics;2018-03

2. On a Class of Bivariate Mixed Sarmanov Distributions;SSRN Electronic Journal;2018

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