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Book
Introduction à la théorie des groupes
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Year: 1965 Publisher: Paris Dunod

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Book
Groupoïdes
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Year: 1965 Publisher: Bruxelles Editions "Labor "

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Book
Groupes
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Year: 1967 Publisher: Bruxelles Paris Presses universitaires de Bruxelles Dunod

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Book
Généralisations des groupes projectifs basées sur leurs propriétés de transitivité
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Year: 1952 Publisher: Bruxelles Palais des Académies

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Mastering MATLAB: a comprehensive tutorial and reference
Authors: ---
ISBN: 0131915940 9780131915947 Year: 1996 Publisher: Upper Saddle River (N.J.): Prentice Hall,

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Mastering MATLAB 6 : a comprehensive tutorial and reference
Authors: ---
ISBN: 0130194689 0131218522 9780130194688 Year: 2001 Publisher: Upper Saddle River, N.J. : Prentice Hall,

Mathematical explorations with MATLAB
Authors: --- ---
ISBN: 0521639204 0521630789 Year: 1999 Publisher: Cambridge Cambridge University press

Schaum's outline of theory and problems of numerical analysis
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ISBN: 0070552215 Year: 1988 Publisher: New York (N.Y.): McGraw-Hill

Numerical analysis for statisticians.
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ISBN: 0387949798 9780387949796 9780387227245 9786610006885 1280006889 0387227245 Year: 2000 Publisher: New York Springer

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This book, like many books, was born in frustration. When in the fall of 1994 I set out to teach a second course in computational statistics to d- toral students at the University of Michigan, none of the existing texts seemed exactly right. On the one hand, the many decent, even inspiring, books on elementary computational statistics stress the nuts and bolts of using packaged programs and emphasize model interpretation more than numerical analysis. On the other hand, the many theoretical texts in - merical analysis almost entirely neglect the issues of most importance to statisticians. TheclosestbooktomyidealwastheclassicaltextofKennedy and Gentle [2]. More than a decade and a half after its publication, this book still has many valuable lessons to teach statisticians. However, upon re?ecting on the rapid evolution of computational statistics, I decided that the time was ripe for an update. The book you see before you represents a biased selection of those topics in theoretical numerical analysis most relevant to statistics. By intent this book is not a compendium of tried and trusted algorithms, is not a c- sumer’s guide to existing statistical software, and is not an exposition of computer graphics or exploratory data analysis. My focus on principles of numerical analysis is intended to equip students to craft their own software and to understand the advantages and disadvantages of di?erent numerical methods. Issues of numerical stability, accurate approximation, compu- tional complexity, and mathematical modeling share the limelight and take precedence over philosophical questions of statistical inference.

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