- Series: Chapman & Hall/CRC The R Series (Book 17)
- Hardcover: 656 pages
- Publisher: Chapman and Hall/CRC; 1 edition (August 26, 2014)
- Language: English
- ISBN-10: 1466592591
- ISBN-13: 978-1466592599
- Product Dimensions: 7.2 x 1.5 x 10.2 inches
- Shipping Weight: 2.9 pounds (View shipping rates and policies)
- Average Customer Review: 4 customer reviews
- Amazon Best Sellers Rank: #1,256,521 in Books (See Top 100 in Books)
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Computational Actuarial Science with R (Chapman & Hall/CRC The R Series) 1st Edition
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"… the main objective of the book is that the reader gets interested in the topic and plays with the presented models and R codes in an active way. I have experienced that this goal can be easily reached for a large audience of readers because the presentation of the various arguments encourages an active learning of the concepts ‘without being burdened by the theory.’"
―International Statistical Review, 83, 2015
"… worthwhile reading and can be recommended to anyone who is interested in the computational aspects of actuarial science. The book contains many detailed worked examples, with R code fully integrated into the text. … the book provides information and code that readers with any quantitative background can gain something from. It will naturally appeal to actuaries of all calibers, but it has a much wider audience of quantitative analysts using R for statistical modeling and data analysis in various fields. There are also good reasons to recommend this book to any science library."
―Journal of the Royal Statistical Society, Series A, 2015
About the Author
Arthur Charpentier is a professor of actuarial science at the University of Québec at Montréal. He is a fellow of the French Institute of Actuaries and holds a PhD in applied mathematics from K.U. Leuven. Dr. Charpentier is the co-author of two textbooks on mathematical models of nonlife insurance and has published several articles in peer-reviewed journals. He is also the editor of the blog freakonometrics.hypotheses.org
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One thing I found difficult is the dataset. After looking around I found a download site for installing the dataset package, but still could not find dataset for chapter 14, for example. I found one github site for source code, but that is incomplete. The book would be more approachable if its supplemental materials are made easily available.
I do modeling work in operational risk and this book is perfect for working with R. Looking forward to Dr. Charpentier's next work.
The printing has many faded parts but anything from it (the content) is supperb