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: Computational Actuarial Science with R
: Arthur Charpentier
: Chapman and Hall/CRC
: The R Series
ISBN: 1466592591
: 2014
: 656
:
: pdf (true)
: 15.0 MB

A Hands-On Approach to Understanding and Using Actuarial Models.

Computational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/C++ embedded codes.

R includes a wide range of standard statistical functions and contributed packages that extend the range of routine functions, including graphical methods. And once we get used to it, R is an easy and intuitive programming language. In the statistical literature, new methods are often accompanied by implementation in R, so that R became a sort of "lingua franca" in the statistical community (including connected areas, from social science to finance, and actuarial science).

After an introduction to the R language, the book is divided into four parts. The first one addresses methodology and statistical modeling issues. The second part discusses the computational facets of life insurance, including life contingencies calculations and prospective life tables. Focusing on finance from an actuarial perspective, the next part presents techniques for modeling stock prices, nonlinear time series, yield curves, interest rates, and portfolio optimization. The last part explains how to use R to deal with computational issues of nonlife insurance.

Taking a do-it-yourself approach to understanding algorithms, this book demystifies the computational aspects of actuarial science. It shows that even complex computations can usually be done without too much trouble. Datasets used in the text are available in an R package (CASdatasets) from CRAN.

Computational Actuarial Science with R












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