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Bayesian Statistics in Actuarial Science

with Emphasis on Credibility

  • Book
  • © 1992

Overview

Authors:
  1. Stuart A. Klugman

    1. Drake University, USA

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Introduction

    • Stuart A. Klugman
    Pages 1-3

  3. Bayesian Statistical Analysis

    • Stuart A. Klugman
    Pages 5-16

  4. Computational Aspects of Bayesian Analysis

    • Stuart A. Klugman
    Pages 17-35

  5. Prediction with Parameter Uncertainty

    • Stuart A. Klugman
    Pages 37-55

  6. The Credibility Problem

    • Stuart A. Klugman
    Pages 57-64

  7. The Hierarchical Bayesian Approach

    • Stuart A. Klugman
    Pages 65-79

  8. The Hierarchical Normal Linear Model

    • Stuart A. Klugman
    Pages 81-113

  9. Examples

    • Stuart A. Klugman
    Pages 115-149

  10. Modifications to the Hierarchical Normal Linear Model

    • Stuart A. Klugman
    Pages 151-157

  11. Back Matter

    Pages 159-237
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About this book

The debate between the proponents of "classical" and "Bayesian" statistica} 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. While the examples are all actuarial in nature, the methods discussed are applicable to any structured estimation problem. In particular, statisticians will recognize that the basic credibility problem has the same setting as the random effects model from analysis of variance.

Authors and Affiliations

  • Drake University, USA

    Stuart A. Klugman

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