Bayesian Statistics in Actuarial Science: With Emphasis on Credibility

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
PublishedOn
2010-10-28
Title
Bayesian Statistics in Actuarial Science: With Emphasis on Credi
Artist
Not Specified
ISBN
9789048157907
Subject Area
Mathematics, Business & Economics
Publication Name
Bayesian Statistics in Actuarial Science : with Emphasis on Credibility
Publisher
Springer Netherlands
Item Length
9.3 in
Subject
Probability & Statistics / General, Finance / General, Management Science, Insurance / General, Probability & Statistics / Bayesian Analysis
Publication Year
2010
Series
HÜBNER International Series on Risk, Insurance and Economic Security Ser.
Type
Textbook
Format
Trade Paperback
Language
English
Author
Stuart A. Klugman
Item Weight
14 Oz
Item Width
6.1 in
Number of Pages
Xiv, 238 Pages

About this product

Product Identifiers

Publisher
Springer Netherlands
ISBN-10
9048157900
ISBN-13
9789048157907
eBay Product ID (ePID)
109053156

Product Key Features

Number of Pages
Xiv, 238 Pages
Publication Name
Bayesian Statistics in Actuarial Science : with Emphasis on Credibility
Language
English
Subject
Probability & Statistics / General, Finance / General, Management Science, Insurance / General, Probability & Statistics / Bayesian Analysis
Publication Year
2010
Type
Textbook
Subject Area
Mathematics, Business & Economics
Author
Stuart A. Klugman
Series
HÜBNER International Series on Risk, Insurance and Economic Security Ser.
Format
Trade Paperback

Dimensions

Item Weight
14 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
Dewey Edition
20
Series Volume Number
15
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
368/.01
Table Of Content
1. Introduction.- 2. Bayesian Statistical Analysis.- 3. Computational Aspects of Bayesian Analysis.- 4. Prediction with Parameter Uncertainty.- 5. The Credibility Problem.- 6. The Hierarchical Bayesian Approach.- 7. The Hierarchical Normal Linear Model.- 8. Examples.- 9. Modifications to the Hierarchical Normal Linear Model.- Appendix. Algorithms, Programs, and Data Sets.- A. The Simplex Method of Function Maximization.- B. Adaptive Gaussian Integration.- C. Gauss-Hermite Integration.- D. Polar Method for Generating Normal Deviates.- E. GAUSS Programs.- 1. Simplex Maximization.- 2. Adaptive Gaussian Integration.- 3. Gauss-Hermite Integration.- 4. Monte Carlo Integration.- 5. Tierney-Kadane Integration.- F. Data Sets.- 1. Data Set 1.- 2. Data Sets 2-4.
Synopsis
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.
LC Classification Number
HF4999.2-6182

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