Operations Research and Information Engineering is the science of rational decision making and the study, design and integration of complex situations and systems with the goal of predicting system behavior and improving or optimizing system performance. It encompasses managerial decision making, mathematical and computer modeling and the use of information technology for informed decision-making.

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  • Extreme value analysis without the largest values: what can be done? 

    Zou, Jingjing; Davis, Richard; Samorodnitsky, Gennady (2017)
    In this paper we are concerned with the analysis of heavy-tailed data when a portion of the extreme values are unavailable. This research was motivated by an analysis of the degree distributions in a large social network. ...
  • Extremal theory for long range dependent infinitely divisible processes 

    Samorodnitskty, Gennady; Wang, Yizao (2017-03)
    We prove limit theorems of an entirely new type for certain long memory regularly varying stationary \id\ random processes. These theorems involve multiple phase transitions governed by how long the memory is. Apart ...
  • Distance covariance for stochastic processes 

    Matsui, Muneya; Mikosch, Thomas; Samorodnitsky, Gennady (2016-12-13)
    The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We ...
  • Closed-form Ruin Probabilities in Classical Risk Models with Gamma Claims 

    Constantinescu, Corina; Samorodnitsky, Gennady; Zhu, Wei (2016-12-12)
    In this paper we provide three equivalent expressions for ruin probabilities in a Cram\'er-Lundberg model with gamma distributed claims. The results are solutions of integro-differential equations, derived by means of ...
  • Extreme values of the uniform autoregressive processes and missing observations 

    Glavas, Lenka; Mladenovic, Pavle; Samorodnitsky, Gennady (2016)
    We investigate partial maxima of the uniform AR(1) processes with parameter r geq 2. Positively and negatively correlated processes are considered. New limit theorems for maxima in complete and incomplete samples are obtained

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