國立虎尾科技大學 |

Generalized linear models for insurance data /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Generalized linear models for insurance data // Piet de Jong, Gillian Z. Heller.
作者:	Jong, Piet de,
其他作者:	Heller, Gillian Z.,
面頁冊數:	1 online resource (x, 196 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Linear models (Statistics) -
電子資源:	https://doi.org/10.1017/CBO9780511755408
ISBN:	9780511755408 (ebook)

Generalized linear models for insurance data /
Jong, Piet de,

Generalized linear models for insurance data /Piet de Jong, Gillian Z. Heller. - 1 online resource (x, 196 pages) :digital, PDF file(s). - International series on actuarial science. - International series on actuarial science..

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.

ISBN: 9780511755408 (ebook)Subjects--Topical Terms:

632956
Linear models (Statistics)

LC Class. No.: HG8782 / .J66 2008

Dewey Class. No.: 368.01

Generalized linear models for insurance data /
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