Numerical Methods of Statistics
Numerical Methods of Statistics
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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.
- Lots of exercises, ranging from elementary to research-level problems
- Accompanying computer code
- Useful both as text or reference book
Reviews & endorsements
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
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: '… 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
Product details
May 2012Adobe eBook Reader
9781139244398
0 pages
0kg
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- 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.
