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Communications in Statistics - Theory and Methods Volume 40, 2011 - Issue 4
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Original Articles

A Semi-Nonparametric Approach to Model Panel Count Data

Jean-Philippe Boucher Département de Mathématiques, Université du Québec à Montréal, Quebec, CanadaCorrespondence[email protected]
&
Montserrat Guillen Department of Econometrics, RFA-IREA, University of Barcelona, Barcelona, Spain
Pages 622-634 | Received 20 Nov 2008, Accepted 27 Oct 2009, Published online: 02 Dec 2010

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Read on this site (2)

Hong Li, Yang Lu & Wenjun Zhu. (2021) Dynamic Bayesian Ratemaking: A Markov Chain Approximation Approach. North American Actuarial Journal 25:2, pages 186-205.
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Peng Shi & EmilianoA. Valdez. (2014) Longitudinal modeling of insurance claim counts using jitters. Scandinavian Actuarial Journal 2014:2, pages 159-179.
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Articles from other publishers (6)

Gee Y. Lee & Peng Shi. (2019) A dependent frequency–severity approach to modeling longitudinal insurance claims. Insurance: Mathematics and Economics 87, pages 115-129.
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Xin Ye, Ke Wang, Yajie Zou & Dominique Lord. (2018) A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data. PLOS ONE 13:5, pages e0197338.
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Imen Karaa & Habib Chabchoub. (2018) Zero-inflated and over-dispersed data models: Empirical evidence from insurance claim frequencies. Assurances et gestion des risques 84:3-4, pages 103-128.
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Jilber Urbina & Montserrat Guillén. (2014) An application of capital allocation principles to operational risk and the cost of fraud. Expert Systems with Applications 41:16, pages 7023-7031.
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Xiaobing Zhao & Xian Zhou. (2012) Copula models for insurance claim numbers with excess zeros and time-dependence. Insurance: Mathematics and Economics 50:1, pages 191-199.
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Hong Li, Yang Lu & Wenjun Zhu. (2019) Dynamic Bayesian Ratemaking: A Markov Chain Approximation Approach. SSRN Electronic Journal.
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