Abstract

Journal of Actuarial Practice

Volume 12, 2005


Modeling Insurance Loss Data: The Log-EIG Distribution

Uditha Balasooriya, C.-K. Low, and Adrian Y.W. Wong

Abstract

The log-EIG distribution was recently introduced to the probability literature. It has positive support and a moderately long tail, and is closer to the lognormal than to the gamma or Weibull distributions. Our simulations show that data generated from a log-EIG distribution cannot be adequately described by lognormal, gamma, or Weibull distributions. The log-EIG distribution is a worthwhile candidate for modeling insurance claims (loss) data or lifetime data. Examples of fitting the log-EIG to published insurance claims data are given.

Key words and phrases: claims distribution, optimal invariant selection procedure, Akaike information criterion, simulation, fitting distributions

Corresponding Author:

Uditha Balasooriya

S3-B2B-57,

Nanyang Business School,

Nanyang Technological University,

Nanyang Avenue,

SINGAPORE 639798

E-mail: auditha@ntu.edu.sg


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