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Much of this book is concerned with autoregressive and moving av erage linear stationary sequences and random fields. Chapter 1 considers the question of reversibility for linear stationary sequences and gives necessary and sufficient conditions for the reversibility.
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This is a volume consisting of selected papers that were presented at the 3rd St. Petersburg Workshop on Simulation held at St. Petersburg, Russia, during June 28-July 3, 1998.
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The articles in this volume were contributed by the friends of Lucien Le Cam on the occasion of his 70th birthday in November 1994. In addition to the 29 contributed articles, we have included a short vita, a list of publications, and a list of Lucien's Ph.D.
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Other goals are to edit the known results in a unified manner, classify them and identify where and how they relate to each other, and... Læs mere
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1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including... Læs mere
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Included are finite probability spaces, com binatorics, set theory, independence and conditional probability, random variables, Chebyshev's theorem, the law of large... Læs mere
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Statistical methods are becoming more important in all biological fields of study. The chapters cover a broad spectrum of topics and bridge the gap between introductory biological statistics and advanced approaches such as multivariate techniques and nonlinear models.
Bemærk: Kan ikke leveres før jul.
Bemærk: Kan ikke leveres før jul.
The book is devoted to the study of important classes of stochastic processes: discrete and continuous time Markov processes, Poisson processes, renewal and regenerative processes, semi-Markov processes, queueing models, and diffusion processes.
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The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and... Læs mere
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This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works.
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This book provides a comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes.