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“My main take away is that these authors spend a lot of time thinking about issues that I never think about. They argue strongly that I, as a statistician, should think about them more, and I find their argument compelling. I certainly enjoyed the various flashes of insight into computation I had as I read their book. … The book’s case studies … are incredibly detailed and deep, far beyond the case studies typically used to illustrate these methods. … I greatly enjoyed the overall arc of the book and found it quite compelling. … a nice book to have on the shelf in case you find yourself suspicious about something computational, or want to find a case study illustrating some topic in computation.”
―Luke W. Miratrix, Journal of the American Statistical Association, March 2015
"… it provides the necessary skills to construct statistical algorithms and hence to contribute to statistical computing. And I wish I had the luxury to teach from Foundations of Statistical Algorithms to my graduate students … a rich book that should benefit a specific niche of statistical graduates and would-be-statisticians, namely those ready to engage into serious statistical programming. It should provide them with the necessary background, out of which they should develop their own tools."
―Christian Robert on his blog, February 2014
"The book is suitable for readers who not only want to understand current statistical algorithms, but also gain a deeper understanding of how the algorithms are constructed and how they operate. It is addressed first and foremost to students and lecturers teaching the foundations of statistical algorithms."
―Ivan Křivý, Zentralblatt MATH 1296