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Modeling and Evaluating Insurance Losses Via Mixtures of Erlang Distributions

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  • Simon Lee
  • X. Lin

Abstract

In this paper we suggest the use of mixtures of Erlang distributions with common scale parameter to model insurance losses. A modified expectation-maximization (EM) algorithm for parameter estimation tailored to this class of distributions is presented, and its computation efficiency is discussed. Goodness-of-fit tests are performed for data generated from some common parametric distributions and for catastrophic loss data in the United States. Formulas for value-at-risk and conditional tail expectation are provided for individual and aggregate losses.

Suggested Citation

  • Simon Lee & X. Lin, 2010. "Modeling and Evaluating Insurance Losses Via Mixtures of Erlang Distributions," North American Actuarial Journal, Taylor & Francis Journals, vol. 14(1), pages 107-130.
    • Handle: RePEc:taf:uaajxx:v:14:y:2010:i:1:p:107-130
    DOI: 10.1080/10920277.2010.10597580
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