Numerical Methods of Statistics (Cambridge Series in Statistical and Probabi...
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eBay-Artikelnr.:236100260850
Artikelmerkmale
- Artikelzustand
- Release Year
- 2001
- Book Title
- Numerical Methods of Statistics (Cambridge Series in Statistic...
- ISBN
- 9780521791687
Über dieses Produkt
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
0521791685
ISBN-13
9780521791687
eBay Product ID (ePID)
1704274
Product Key Features
Number of Pages
444 Pages
Publication Name
Numerical Methods of Statistics
Language
English
Publication Year
2001
Subject
Probability & Statistics / General, Numerical Analysis, Natural Language Processing
Type
Textbook
Subject Area
Mathematics, Computers
Series
Cambridge Series in Statistical and Probabilistic Mathematics Ser.
Format
Hardcover
Dimensions
Item Height
1.2 in
Item Weight
34.1 Oz
Item Length
10.4 in
Item Width
7.3 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
00-031269
Dewey Edition
21
Reviews
'... a really nice introduction to numerical analysis. All the classical subjects of a numerical analysis course are discussed in a surprisingly short and clear way ... When adapting the examples, the first half of the book can be used as a numerical analysis course for any other discipline ...'. Adhemar Bultheel, Bulletin of the Belgian Mathematical Society, Review of the hardback: '... a really nice introduction to numerical analysis. All the classical subjects of a numerical analysis course are discussed in a surprisingly short and clear way ... When adapting the examples, the first half of the book can be used as a numerical analysis course for any other discipline ...'. Adhemar Bultheel, Bulletin of the Belgian Mathematical Society, Review of the hardback: '… a really nice introduction to numerical analysis. All the classical subjects of a numerical analysis course are discussed in a surprisingly short and clear way … When adapting the examples, the first half of the book can be used as a numerical analysis course for any other discipline …'. Adhemar Bultheel, Bulletin of the Belgian Mathematical Society, Review of the hardback: '… this book grew out of notes for A Statistical Computing Course … The goal of this course was to prepare the doctoral students with the computing tools needed for statistical research. I very much liked this book and recommend it for this use.' Jaromir Antoch, Zentralblatt fr Mathematik, Review of the hardback: '... this book grew out of notes for A Statistical Computing Course ... The goal of this course was to prepare the doctoral students with the computing tools needed for statistical research. I very much liked this book and recommend it for this use.' Jaromir Antoch, Zentralblatt f r Mathematik, Review of the hardback: '... an excellent tool both for self-study and for classroom teaching. it summarizes the state of the art well and provides a solid basis, through the programs hat go with the book, for numerical experimentation and further development. All in all, this is a good book to have ... I recommend it.' D. Denteneer, Mathematics of Computing, '... an excellent tool both for self-study and for classroom teaching. it summarizes the state of the art well and provides a solid basis, through the programs hat go with the book, for numerical experimentation and further development. All in all, this is a good book to have ... I recommend it.' D. Denteneer, Mathematics of Computing, '... this book grew out of notes for A Statistical Computing Course ... The goal of this course was to prepare the doctoral students with the computing tools needed for statistical research. I very much liked this book and recommend it for this use.' Jaromir Antoch, Zentralblatt für Mathematik, Review of the hardback: '... this book grew out of notes for A Statistical Computing Course ... The goal of this course was to prepare the doctoral students with the computing tools needed for statistical research. I very much liked this book and recommend it for this use.' Jaromir Antoch, Zentralblatt für Mathematik, Review of the hardback: '… an excellent tool both for self-study and for classroom teaching. it summarizes the state of the art well and provides a solid basis, through the programs hat go with the book, for numerical experimentation and further development. All in all, this is a good book to have … I recommend it.' D. Denteneer, Mathematics of Computing
Series Volume Number
Series Number 7
Illustrated
Yes
Dewey Decimal
519.5
Table Of Content
1. Algorithms and computers; 2. Computer arithmetic; 3. Matrices and linear equations; 4. More methods for solving linear equations; 5. Least squares; 6. Eigenproblems; 7. Functions: interpolation, smoothing and approximation; 8. Introduction to optimization and nonlinear equations; 9. Maximum likelihood and nonlinear regression; 10. Numerical integration and Monte Carlo methods; 11. Generating random variables from other distributions; 12. Statistical methods for integration and Monte Carlo; 13. Markov chain Monte Carlo methods; 14. Sorting and fast algorithms.
Synopsis
This 2001 book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods; for mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems., This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. The book concludes with an examination of sorting, FFT and the application of other "fast" algorithms to statistics. Each chapter contains exercises that range in difficulty as well as examples of the methods at work. Most of the examples are accompanied by demonstration code available from the author's home page., This 2001 book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods; for mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book provides a basic background in numerical analysis emphasizing issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats application of numerical tools: numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. The book concludes with an examination of sorting, FFT and the application of other 'fast' algorithms to statistics. Each chapter contains exercises that range from the simple to research problems, as well as examples of the methods at work.
LC Classification Number
QA276.4 .M65 2001
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