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Setting the price of a non-life insurance policy involves the statistical analysis of insurance data, taking into consideration various properties of the insured object and the policy holder. Introduced by British actuaries, generalized linear models (GLMs) have by now become a standard approach used for pricing in many countries. The book focuses on methods based on GLMs that have been found useful in actuarial practice. Basic theory of GLMs in an insurance setting is presented, with useful extensions that are not in common use. The book can be used in actuarial education designed to meet the…mehr

Produktbeschreibung
Setting the price of a non-life insurance policy involves the statistical analysis of insurance data, taking into consideration various properties of the insured object and the policy holder. Introduced by British actuaries, generalized linear models (GLMs) have by now become a standard approach used for pricing in many countries. The book focuses on methods based on GLMs that have been found useful in actuarial practice. Basic theory of GLMs in an insurance setting is presented, with useful extensions that are not in common use. The book can be used in actuarial education designed to meet the European Core Syllabus and is written for actuarial students as well as practicing actuaries. To support the readers, it contains case studies using real data of some complexity that are available on the www.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Rezensionen
From the reviews:
"This book presents the basic theory of generalized linear models (GLMs) in a tariff analysis setting and also gives some useful extension of standard GLM theory. Many theoretical results of this book are supplemented by several examples and numerical illustrations. Plenty of useful exercises finish each chapter of the book. The textbook is intended for practicing actuaries and actuarial students with a background in mathematics and mathematical statistics." (Jonas Siaulys, Zentralblatt MATH, Vol. 1194, 2010)