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Advances in Mathematical and Statistical Modeling 2008 Edition
Contributor(s): Arnold, Barry C. (Editor), Balakrishnan, N. (Editor), Sarabia Alegria, Jose-Maria (Editor)

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ISBN: 0817646256     ISBN-13: 9780817646257
Publisher: Birkhauser
OUR PRICE: $142.49  

Binding Type: Hardcover
Published: September 2008

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Additional Information
BISAC Categories:
- Mathematics | Probability & Statistics - General
- Mathematics | Applied
- Mathematics | Linear & Nonlinear Programming
Dewey: 519.502
LCCN: 2007941545
Series: Statistics for Industry and Technology
Physical Information: 1" H x 7" W x 10.2" (1.85 lbs) 368 pages
Features: Bibliography, Index
Descriptions, Reviews, Etc.
Publisher Description:
Enrique Castillo is a leading figure in several mathematical, statistical, and engineering fields, having contributed seminal work in such areas as statistical modeling, extreme value analysis, multivariate distribution theory, Bayesian networks, neural networks, functional equations, artificial intelligence, linear algebra, optimization methods, numerical methods, reliability engineering, as well as sensitivity analysis and its applications. Organized to honor Castillo's significant contributions, this volume is an outgrowth of the International Conference on Mathematical and Statistical Modeling and covers recent advances in the field. Also presented are applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques.

The book is divided into nine major sections:

* Distribution Theory and Applications

* Probability and Statistics

* Order Statistics and Analysis

* Engineering Modeling

* Extreme Value Theory

* Business and Economics Applications

* Statistical Methods

* Applied Mathematics

* Discrete Distributions

This comprehensive reference work will appeal to a diverse audience from the statistical, applied mathematics, engineering, and economics communities. Practitioners, researchers, and graduate students in mathematical and statistical modeling, optimization, and computing will benefit from this work.

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