September 2012
Beginner to intermediate
536 pages
14h 40m
English
book
Loss Models: From Data to Decisions, 4th Edition
by Stuart A. Klugman, Harry H. Panjer, Gordon E. Willmot
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13.1 Method of moments and percentile matching
For these methods we assume that all n observations are from the same parametric distribution. In particular, let the distribution function be given by
where θT is the transpose of θ. That is, θ is a column vector containing the p parameters to be estimated. Furthermore, let 
be the kth raw moment, and let πg (θ) be the 100gth percentile of the random variable. That is, F
. If the distribution function is continuous, there will be at least one solution to that equation.
For a sample of n independent observations from this random variable, let 
be the empirical estimate of the kth moment and let 
be the empirical estimate of the 100gth percentile
Definition 13.1 A method-of-moments estimate of θ is any solution of the p equations
The motivation for this estimator is that it produces a model that has the same first p raw moments as the data (as ...
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