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Advances in Mathematical and Statistical Modeling (Statistics for Industry and Technology)

Advances in Mathematical and Statistical Modeling (Statistics for Industry and Technology)

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Creators: Barry C. Arnold, N. Balakrishnan, Jose Maria Sarabia, Roberto Minguez
Publisher: Birkhaeuser Boston
Category: Book

Buy New: $99.00



New (8) from $99.00

Sales Rank: 7174894

Media: Hardcover
Edition: 1
Number Of Items: 1
Pages: 368
Shipping Weight (lbs): 2
Dimensions (in): 10 x 7.1 x 1

ISBN: 0817646256
Dewey Decimal Number: 519
EAN: 9780817646257
ASIN: 0817646256

Publication Date: September 2, 2008
Availability: Usually ships in 24 hours

Editorial Reviews:

Product 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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