2005, ISBN: 9780471669838
ID: 574768523
A complete, self-contained introduction to matrix analysis theory and practice Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. This updated second edition of Matrix Analysis for Statistics offers readers a unique, unified view of matrix analysis theory and methods. Matrix Analysis for Statistics, Second Edition provides in-depth, step-by-step coverage of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; the distribution of quadratic forms; and more. The subject matter is presented in a theorem/proof format, allowing for a smooth transition from one topic to another. Proofs are easy to follow, and the author carefully justifies every step. Accessible even for readers with a cursory background in statistics, yet rigorous enough for students in statistics, this new edition is the ideal introduction to matrix analysis theory and practice. The book features: * Self-contained chapters, which allow readers to select individual topics or use the reference sequentially * Extensive examples and chapter-end practice exercises, many of which involve the use of matrix methods in statistical analyses * New material on elliptical distributions and new expanded coverage of such topics as eigenvalue inequalities and matrices partitioned in 2 by 2 form, in particular, results relating the rank, generalized inverse, eigenvalues of such matrices to their submatrices, and much more * Optional sections for mathematically advanced readers Matrix Analysis for Statistics Bücher > Fremdsprachige Bücher > Englische Bücher gebundene Ausgabe 11.02.2005, Wiley John + Sons, .200
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ISBN: 9780471669838
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A complete, self-contained introduction to matrix analysis theory and practice Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. This updated second edition of Matrix Analysis for Statistics offers readers a unique, unified view of matrix analysis theory and methods. Matrix Analysis for Statistics, Second Edition provides in-depth, step-by-step coverage of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; the distribution of quadratic forms; and more. The subject matter is presented in a theorem/proof format, allowing for a smooth transition from one topic to another. Proofs are easy to follow, and the author carefully justifies every step. Accessible even for readers with a cursory background in statistics, yet rigorous enough for students in statistics, this new edition is the ideal introduction to matrix analysis theory and practice. The book features: * Self-contained chapters, which allow readers to select individual topics or use the reference sequentially * Extensive examples and chapter-end practice exercises, many of which involve the use of matrix methods in statistical analyses * New material on elliptical distributions and new expanded coverage of such topics as eigenvalue inequalities and matrices partitioned in 2 by 2 form, in particular, results relating the rank, generalized inverse, eigenvalues of such matrices to their submatrices, and much more * Optional sections for mathematically advanced readers Matrix Analysis for Statistics Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, Wiley John + Sons
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A complete, self-contained introduction to matrix analysis theory and practice Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. This updated second edition of Matrix Analysis for Statistics offers readers a unique, unified view of matrix analysis theory and methods. Matrix Analysis for Statistics, Second Edition provides in-depth, step-by-step coverage of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; the distribution of quadratic forms; and more. The subject matter is presented in a theorem/proof format, allowing for a smooth transition from one topic to another. Proofs are easy to follow, and the author carefully justifies every step. Accessible even for readers with a cursory background in statistics, yet rigorous enough for students in statistics, this new edition is the ideal introduction to matrix analysis theory and practice. The book features: Self-contained chapters, which allow readers to select individual topics or use algebra,algebra and trigonometry,applied,linear,mathematics,matrices,probability and statistics,pure mathematics,science and math,science and math Statistics, Wiley-Interscience
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"Matrix Analysis for Statistics, Second Edition" provides in-depth, step-by-step coverage of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors, the Moore-Penrose inverse, matrix differentiation, the distribution of quadratic forms, and more. The subject matter is presented in a theorem/proof format, allowing for a smooth transition from one topic to another. Proofs are easy to follow, and the author carefully justifies every step. Accessible even for readers with a cursory background in statistics, yet rigorous enough for students in statistics, this new edition is the ideal introduction to matrix analysis theory and practice. Matrix Analysis for Statistics Schott, James R. / Schott, Wiley-Interscience
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[SR: 1163918], Gebundene Ausgabe, [EAN: 9780471669838], John Wiley & Sons, John Wiley & Sons, Book, [PU: John Wiley & Sons], John Wiley & Sons, 56254011, Wahrscheinlichkeit & Statistik, 56248011, Angewandte Mathematik, 56214011, Mathematik, 56047011, Wissenschaft, 54071011, Genres, 52044011, Fremdsprachige Bücher, 56218011, Matrizen, 56214011, Mathematik, 56047011, Wissenschaft, 54071011, Genres, 52044011, Fremdsprachige Bücher, 56231011, Algebra, 56230011, Reine Mathematik, 56214011, Mathematik, 56047011, Wissenschaft, 54071011, Genres, 52044011, Fremdsprachige Bücher
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Title: | Matrix Analysis for Statistics |
ISBN: | 9780471669838 |
Details of the book - Matrix Analysis for Statistics
EAN (ISBN-13): 9780471669838
ISBN (ISBN-10): 0471669830
Hardcover
Publishing year: 2005
Publisher: John Wiley & Sons
480 Pages
Weight: 0,866 kg
Language: eng/Englisch
Book in our database since 23.05.2007 01:54:35
Book found last time on 29.09.2016 13:19:09
ISBN/EAN: 9780471669838
ISBN - alternate spelling:
0-471-66983-0, 978-0-471-66983-8
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