Cantitate/Preț
Produs

Modern Actuarial Risk Theory: Using R

Autor Rob Kaas, Marc Goovaerts, Jan Dhaene, Michel Denuit
en Limba Engleză Paperback – 30 sep 2009
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.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 70190 lei  6-8 săpt.
  Springer Berlin, Heidelberg – 30 sep 2009 70190 lei  6-8 săpt.
Hardback (1) 95556 lei  6-8 săpt.
  Springer Berlin, Heidelberg – 25 aug 2008 95556 lei  6-8 săpt.

Preț: 70190 lei

Preț vechi: 82577 lei
-15% Nou

Puncte Express: 1053

Preț estimativ în valută:
13433 13972$ 11089£

Carte tipărită la comandă

Livrare economică 12-26 aprilie

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783642034077
ISBN-10: 3642034071
Pagini: 400
Ilustrații: XVIII, 382 p.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.56 kg
Ediția:2nd ed. 2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Recenzii

From the reviews of the second edition:
"The book gives a comprehensive survey of non-life insurance mathematics. … Originally written for use with the actuarial science programs at the Universities of Amsterdam and Leuven, it is now in use at many other universities as well as for the non-academic actuarial education program organized by the Dutch Actuarial Society. The methods presented can not only be used in non-life insurance, but also in other branches of actuarial science, as well as in actuarial practice." (Pavel Stoynov, Zentralblatt MATH, Vol. 1148, 2008)
“This book gives an introduction to non-life insurance mathematics. … Throughout the book, the software R is used for the implementation of the techniques presented. One finds also many exercises with hints for their solution in an appendix.” (F. Hofbauer, Monatshefte für Mathematik, Vol. 161 (1), August, 2010)

Textul de pe ultima copertă

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.
 

Caracteristici

Reflects the state of the art in actuarial risk theory Uses R, the de facto standard for statistical computation, for the illustration of the techniques applied Presents practical paradigms in insurance as well as numerous exercises with solutions Includes supplementary material: sn.pub/extras