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Fitting the Truncated Pareto Distribution to Loss Distributions

Published online by Cambridge University Press:  11 August 2014

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Hogg and Klugman use the truncated Pareto distribution with probability density function

where δ≥0 is specified and α > 0 and λ > 0 are unknown parameters, to describe insurance claims. This is fitted first of all by the method of moments, using the estimators

and

where is the mean of a simple random sample, and the (biased) variance

The authors then suggest, on pp. 113–16, that these estimates be used as starting values in a Newton iteration to get the maximum likelihood estimates of the parameters, but this technique can fail as a result of convergence problems. The object of this note is to show that this has led Hogg and Klugman to underestimate seriously the area in the tail of a fitted loss distribution, and to discuss a method of circumventing this difficulty.

Type
Research Article
Copyright
Copyright © Staple Inn Actuarial Society 1988

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References

(1) Hogg, R. V. and Klugman, S. A. (1984) Loss Distributions. Wiley.Google Scholar
(2) Walsh, G. R. (1975) Methods of Optimisation. Wiley.Google Scholar
(3) Bunday, B. D. (1984) Basic Optimisation Methods. Arnold, London.Google Scholar