By Arthur Charpentier
ISBN-10: 1466592591
ISBN-13: 9781466592599
ISBN-10: 1466592605
ISBN-13: 9781466592605
A Hands-On method of figuring out and utilizing Actuarial Models
Computational Actuarial technological know-how with R offers an creation to the computational facets of actuarial technology. utilizing uncomplicated R code, the publication is helping you know the algorithms all in favour of actuarial computations. It additionally covers extra complicated issues, akin to parallel computing and C/C++ embedded codes.
After an advent to the R language, the e-book is split into 4 components. the 1st one addresses technique and statistical modeling concerns. the second one half discusses the computational aspects of lifestyles coverage, together with lifestyles contingencies calculations and potential existence tables. concentrating on finance from an actuarial viewpoint, the subsequent half offers suggestions for modeling inventory costs, nonlinear time sequence, yield curves, rates of interest, and portfolio optimization. The final half explains the best way to use R to accommodate computational problems with nonlife insurance.
Taking a homemade method of realizing algorithms, this e-book demystifies the computational facets of actuarial technology. It indicates that even complicated computations can often be refrained from an excessive amount of difficulty. Datasets utilized in the textual content come in an R package deal (CASdatasets) from CRAN.
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Extra info for Computational Actuarial Science with R
Example text
Time series of the Nelson–Siegel coefficients. . . . . . . . . Observed versus fitted yield curves at different periods. . . . . . 1 Cumulated performance of the equally weighted portfolio with an initial wealth of $1000. . . . . . . . . . . . . . . . . Solution of the MV portfolio with the equally weighted portfolio return as target return, and with the smallest mean return as target return. . . Weights of the MV portfolio with the classical and robust covariance estimator.
6 More Complex Graphs . . . . . . . . . . . . . . . . . . . More Advanced R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Memory Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Parallel R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Interfacing R and C/C++ . . . . . . . . . . . . . . . . . . . . . . .
Ending an R Session . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 R for Actuarial Science? org/, R is an “open source software package, licensed under the GNU General Public License” (the so-called GPL). This simply means that R can be installed for free on most desktop and server machines. This platform independence and the open-source philosophy make R an ideal environment for reproducible research.
Computational Actuarial Science with R by Arthur Charpentier
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