On composite lognormal-pareto models

  • Scollnik D
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Abstract

Recently, Cooray & Ananda (2005) proposed a composite lognormal-Pareto model for use with loss payments data of the sort arising in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density thereafter. Here we identify and discuss limitations of this composite lognormal-Pareto model which are likely to severely curtail its potential for practical application to real world data sets. In addition, we present two different composite models based on lognormal and Pareto models in order to address these concerns. The performance of all three composite models is discussed and compared in the context of an example based upon a well-known fire insurance data set.

Author-supplied keywords

  • Danish data
  • Lognormal distribution
  • Mixture model
  • Pareto distribution
  • Predictive modelling
  • Spliced model
  • Truncated

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Authors

  • David P.M. Scollnik

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