Stochastic Orders in Reliability and Risk : In Honor of Professor Moshe Shaked

Stochastic Orders in Reliability and Risk Management is composed of 19 contributions on the theory of stochastic orders, stochastic comparison of order statistics, stochastic orders in reliability and risk analysis, and applications. These review/exploratory chapters present recent and current research on stochastic orders reported at the International Workshop on Stochastic Orders in Reliability and Risk Management, or SORR2011, which took place in the City Hotel, Xiamen, China, from June 27 to June 29, 2011. The conference’s talks and invited contributions also represent the celebration of Professor Moshe Shaked, who has made comprehensive, fundamental contributions to the theory of stochastic orders and its applications in reliability, queueing modeling, operations research, economics and risk analysis. This volume is in honor of Professor Moshe Shaked. The work presented in this volume represents active research on stochastic orders and multivariate dependence, and exemplifies close collaborations between scholars working in different fields. The Xiamen Workshop and this volume seek to revive the community workshop tradition on stochastic orders and dependence and strengthen research collaboration, while honoring the work of a distinguished scholar.

Haijun Li is a Professor of Mathematics and Statistics at Washington State University, Pullman, WA. He received his Ph.D. in Mathematics from the University of Arizona in 1994. His research interests lie in applied probability and stochastic processes, and his current research focuses on multivariate dependence, extreme value theory and risk analysis.

Xiaohu Li holds a Ph.D. in Mathematics from Lanzhou University, China, where he worked on statistics and probability with applications in reliability and life-testing.  Currently, as an applied statistician, his research focuses on multivariate statistical dependence, copula theory and their applications in survival analysis, actuarial science, financial risk management and network security.