- Hardcover: 350 pages
- Publisher: Wiley; 1 edition (March 12, 2002)
- Language: English
- ISBN-10: 0471494461
- ISBN-13: 978-0471494461
- Product Dimensions: 6.3 x 1 x 9.8 inches
- Shipping Weight: 1.5 pounds (View shipping rates and policies)
- Average Customer Review: 5.0 out of 5 stars See all reviews (2 customer reviews)
- Amazon Best Sellers Rank: #3,008,041 in Books (See Top 100 in Books)
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Comparison Methods for Stochastic Models and Risks 1st Edition
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"…a noteworthy contribution to applied probability, and I would recommend it to anyone interested in applied stochastic modeling." (Journal of the American Statistical Association, June 2005)
“…will replace the excellent but now slightly dated text by Shaked and Shathikumar (1994) as the standard reference on stochastic orders.” (Statistical Papers, Vol.46, No.1, January 2005)
"...provides an up-to-date survey of a notable area..." (Mathematical Reviews, 2003d)
"...discusses the major concepts related to stochastic orders..." (SciTech Book News, Vol. 26, No. 2, June 2002)
"...a very timely and methodically orientated book..." (Zentralblatt Math, Vol.999, No.24, 2002)
From the Back Cover
Stochastic orders are important approximation tools that provide valuable insight into the behaviour of complex stochastic models. Research into stochastic orders is blossoming, with many open problems being studied and a wide range of applications explored. In this book the authors explore the most important concepts of the field, from the basic univariate theory through to the most current applications.
* Comprehensive coverage of the theory and applications of stochastic orders.
* Employs a systematic approach with detailed explanation of each concept.
* Features coverage of univariate and multivariate stochastic orders.
* Covers a range of applications, from queueing theory, reliability theory, statistical physics, actuarial and financial risk, and economics.
* Written by authors with many years experience in researching stochastic orders.
Researchers and graduate students studying stochastic orders will find the comprehensive coverage of the subject ideal for their needs. The range of applications will benefit those working in applied probability and statistics, reliability, actuarial science, economics and finance.
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