Modern Actuarial Risk Theory
Rob Kaas
Sold by BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
AbeBooks Seller since January 11, 2012
New - Soft cover
Condition: New
Ships from Germany to U.S.A.
Quantity: 2 available
Add to basketSold by BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
AbeBooks Seller since January 11, 2012
Condition: New
Quantity: 2 available
Add to basketThis item is printed on demand - it takes 3-4 days longer - Neuware -Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and much expanded edition emphasizes the implementation of these techniques through the use of R. This free but incredibly powerful software is rapidly developing into the de facto standard for statistical computation, not just in academic circles but also in practice. With R, one can do simulations, find maximum likelihood estimators, compute distributions by inverting transforms, and much more. 400 pp. Englisch.
Seller Inventory # 9783642034077
This book presents practical paradigms in insurance as well as numerous exercises with solutions. This second edition emphasizes the implementation of all covered techniques through the use of R, the de facto standard for statistical computation.
Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics.
This second and much expanded edition emphasizes the implementation of these techniques through the use of R. This free but incredibly powerful software is rapidly developing into the de facto standard for statistical computation, not just in academic circles but also in practice. With R, one can do simulations, find maximum likelihood estimators, compute distributions by inverting transforms, and much more.
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