Computational Actuarial Science With R

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Computational Actuarial Science with R

Author	: Arthur Charpentier
Publisher	: CRC Press
Total Pages	: 652
Release	: 2014-08-26
ISBN-10	: 9781498759823
ISBN-13	: 1498759823
Rating	: 4/5 (823 Downloads)

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Book Synopsis Computational Actuarial Science with R by : Arthur Charpentier

Download or read book Computational Actuarial Science with R written by Arthur Charpentier and published by CRC Press. This book was released on 2014-08-26 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Hands-On Approach to Understanding and Using Actuarial ModelsComputational 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/

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Language: en
Pages: 652

Computational Actuarial Science with R

Authors: Arthur Charpentier

Categories: Business & Economics

Type: BOOK - Published: 2014-08-26 - Publisher: CRC Press

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A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of a

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Solutions Manual for Actuarial Mathematics for Life Contingent Risks

Authors: David C. M. Dickson

Categories: Business & Economics

Type: BOOK - Published: 2012-03-26 - Publisher: Cambridge University Press

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"This manual presents solutions to all exercises from Actuarial Mathematics for Life Contingent Risks (AMLCR) by David C.M. Dickson, Mary R. Hardy, Howard Water

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Statistical Computing with R

Authors: Maria L. Rizzo

Categories: Reference

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Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, m

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Authors: Edward W. Frees

Categories: Business & Economics

Type: BOOK - Published: 2014-07-28 - Publisher: Cambridge University Press

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This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive