Numerical Methods of Statistics - John Monahan

Numerical Methods of Statistics

(Autor)

Buch | Hardcover
464 Seiten
2011 | 2nd Revised edition
Cambridge University Press (Verlag)
978-0-521-19158-6 (ISBN)
135,90 inkl. MwSt
This second edition explains how computer software is designed to perform the tasks required for sophisticated statistical analysis.
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. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available from the author's website. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder–Mead search algorithm.

John F. Monahan is a Professor of Statistics at North Carolina State University where he joined the faculty in 1978 and has been a professor since 1990. His research has appeared in numerous computational as well as statistical journals. He is also the author of A Primer on Linear Models (2008).

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.

Reihe/Serie Cambridge Series in Statistical and Probabilistic Mathematics
Verlagsort Cambridge
Sprache englisch
Maße 178 x 254 mm
Gewicht 1020 g
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Statistik
ISBN-10 0-521-19158-0 / 0521191580
ISBN-13 978-0-521-19158-6 / 9780521191586
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
was jeder über Informatik wissen sollte

von Timm Eichstädt; Stefan Spieker

Buch | Softcover (2024)
Springer Vieweg (Verlag)
37,99
Grundlagen – Anwendungen – Perspektiven

von Matthias Homeister

Buch | Softcover (2022)
Springer Vieweg (Verlag)
34,99
Eine Einführung in die Systemtheorie

von Margot Berghaus

Buch | Softcover (2022)
UTB (Verlag)
25,00