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Bayesian Statistics in Actuarial Science: With Emphasis on Credibility
From Introduction: The debate between the proponents of classical and Bayesian
statistical methods continues unabated. It is not the purpose of the text to resolve those issues
but rather to demonstrate that within the realm of actuarial science there are a number of problems
that are particularly suited for Bayesian analysis. This has been apparent to actuaries for a long
time, but the lack of adequate computing power and appropriate algorithms had led to the use of
various approximations.
The two greatest advantages to the actuary of the Bayesian approach are that the method is
independent of the model and that interval estimates are as easy to obtain as point estimates.
The former attribute means that once one learns how to analyze one problem, the solution to
similar, but more complex, problems will be no more difficult. The second one takes on added
significance as the actuary of today is expected to
provide evidence concerning the quality of any estimates.
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