Book Reviews

Numerical Analysis for Statisticians

Kenneth Lange

Numerical Analysis for Statisticians

Hardcover: 620 pages
Publisher: Springer-Verlag; 2nd edition (June 15, 2010)
Language: English
ISBN-10: 1441959440

“In the end, it really is just a matter of choosing the relevant parts of mathematics and ignoring the rest. Of course, the hard part is deciding what is irrelevant.”

I missed the first edition of this book and thus read it with a newcomer’s eyes. Past the initial surprise of discovering it was a mathematics book, rather than an algorithmic book, I became engrossed in my reading. Numerical Analysis for Statisticians is a wonderful book. It provides most of the necessary background in calculus and enough algebra to conduct rigorous numerical analyses of statistical problems. This includes expansions, eigen analysis, optimization, integration, approximation theory, and simulation in fewer than 600 pages. Perhaps because I read this book in my garden, I cannot find any solid fact to grumble about—not even about the Markov chain Monte Carlo chapters. I simply enjoyed Numerical Analysis for Statisticians from beginning until end.

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