Stochastic Orders

  • Moshe Shaked
  • J. George Shanthikumar

Part of the Springer Series in Statistics book series (SSS)

Table of contents

About this book


Stochastic ordering is a fundamental guide for decision making under uncertainty. It is also an essential tool in the study of structural properties of complex stochastic systems. This reference text presents a comprehensive coverage of the various notions of stochastic orderings, their closure properties, and their applications. Some of these orderings are routinely used in many applications in economics, finance, insurance, management science, operations research, statistics, and various other fields of study. And the value of the other notions of stochastic orderings still needs to be explored further.

This book is an ideal reference for anyone interested in decision making under uncertainty and interested in the analysis of complex stochastic systems. It is suitable as a text for advanced graduate course on stochastic ordering and applications.

Moshe Shaked is Professor of Mathematics at the University of Arizona, Tucson, AZ. He has made several fundamental contributions to the development of stochastic ordering and stochastic convexity, with applications in reliability theory and economics. He has published over 150 papers in this and related areas.

J. George Shanthikumar is Professor of Industrial Engineering and Operations Research at the University of California, Berkeley, CA. He has made fundamental contributions to the application of stochastic ordering and stochastic convexity to queueing and related problems that arise in operations research and management science. He has published over 250 papers in this and related fields.


Convexity Monotone decision making form management operations research statistics stochastic systems tool uncertainty

Editors and affiliations

  • Moshe Shaked
    • 1
  • J. George Shanthikumar
    • 2
  1. 1.Department of MathematicsUniversity of ArizonaTucson
  2. 2.Department of Industrial Engineering and Operations ResearchUniversity of California, BerkeleyBerkeley

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media, LLC 2007
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-32915-4
  • Online ISBN 978-0-387-34675-5
  • Series Print ISSN 0172-7397
  • Buy this book on publisher's site