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Modern Actuarial Risk Theory Using R /

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, or...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kaas, Rob (Autor), Goovaerts, Marc (Autor), Dhaene, Jan (Autor), Denuit, Michel (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:2nd ed. 2008.
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Modern Actuarial Risk Theory  |h [electronic resource] :  |b Using R /  |c by Rob Kaas, Marc Goovaerts, Jan Dhaene, Michel Denuit. 
250 |a 2nd ed. 2008. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2008. 
300 |a XVIII, 382 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a Utility theory and insurance -- The individual risk model -- Collective risk models -- Ruin theory -- Premium principles and risk measures -- Bonus-malus systems -- Ordering of risks -- Credibility theory -- Generalized linear models -- IBNR techniques -- More on GLMs -- The 'R' in Modern ART -- Hints for the exercises -- Notes and references. 
520 |a 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. . 
650 0 |a Finance. 
650 0 |a Mathematics. 
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650 0 |a Actuarial science. 
650 0 |a Statistics . 
650 0 |a Social sciences-Mathematics. 
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650 2 4 |a Applications of Mathematics. 
650 2 4 |a Business Mathematics. 
650 2 4 |a Actuarial Mathematics. 
650 2 4 |a Statistics in Business, Management, Economics, Finance, Insurance. 
650 2 4 |a Mathematics in Business, Economics and Finance. 
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700 1 |a Dhaene, Jan.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Denuit, Michel.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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