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A Note on Parameter Estimation in the Composite Weibull–Pareto Distribution

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  • Enrique Calderín-Ojeda

    (Centre for Actuarial Studies, Department of Economics, The University of Melbourne, Melbourne, VIC 3010, Australia)

Abstract

Composite models have received much attention in the recent actuarial literature to describe heavy-tailed insurance loss data. One of the models that presents a good performance to describe this kind of data is the composite Weibull–Pareto (CWL) distribution. On this note, this distribution is revisited to carry out estimation of parameters via mle and mle2 optimization functions in R. The results are compared with those obtained in a previous paper by using the nlm function, in terms of analytical and graphical methods of model selection. In addition, the consistency of the parameter estimation is examined via a simulation study.

Suggested Citation

  • Enrique Calderín-Ojeda, 2018. "A Note on Parameter Estimation in the Composite Weibull–Pareto Distribution," Risks, MDPI, vol. 6(1), pages 1-8, February.
    • Handle: RePEc:gam:jrisks:v:6:y:2018:i:1:p:11-:d:131836
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    References listed on IDEAS

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    1. Moshe Levy, 2009. "Gibrat's Law for (All) Cities: Comment," American Economic Review, American Economic Association, vol. 99(4), pages 1672-1675, September.
    2. Abu Bakar, S.A. & Hamzah, N.A. & Maghsoudi, M. & Nadarajah, S., 2015. "Modeling loss data using composite models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 146-154.
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