An Introduction to Stochastic Orders Book

An Introduction to Stochastic Orders

  • Author : Felix Belzunce
  • Publisher : Academic Press
  • Release Date : 2015-09-29
  • Genre: Mathematics
  • Pages : 174
  • ISBN 10 : 9780128038260
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An Introduction to Stochastic Orders discusses this powerful tool that can be used in comparing probabilistic models in different areas such as reliability, survival analysis, risks, finance, and economics. The book provides a general background on this topic for students and researchers who want to use it as a tool for their research. In addition, users will find detailed proofs of the main results and applications to several probabilistic models of interest in several fields, and discussions of fundamental properties of several stochastic orders, in the univariate and multivariate cases, along with applications to probabilistic models. Introduces stochastic orders and its notation Discusses different orders of univariate stochastic orders Explains multivariate stochastic orders and their convex, likelihood ratio, and dispersive orders

Introduction to Stochastic Processes Book

Introduction to Stochastic Processes

  • Author : Erhan Cinlar
  • Publisher : Courier Corporation
  • Release Date : 2013-02-20
  • Genre: Mathematics
  • Pages : 416
  • ISBN 10 : 9780486276328
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Clear presentation employs methods that recognize computer-related aspects of theory. Topics include expectations and independence, Bernoulli processes and sums of independent random variables, Markov chains, renewal theory, more. 1975 edition.

An Introduction to Stochastic Modeling Book

An Introduction to Stochastic Modeling

  • Author : Howard M. Taylor
  • Publisher : Academic Press
  • Release Date : 2014-05-10
  • Genre: Mathematics
  • Pages : 410
  • ISBN 10 : 9781483269276
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An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Introduction to Stochastic Processes Book

Introduction to Stochastic Processes

  • Author : Erhan Cinlar
  • Publisher : Courier Corporation
  • Release Date : 2013-02-01
  • Genre: Mathematics
  • Pages : 418
  • ISBN 10 : 9780486497976
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This clear presentation of themost fundamental models ofrandom phenomena employsmethods that recognize computerrelatedaspects of theory. Topicsinclude probability spaces andrandom variables, expectationsand independence, Bernoulliprocesses and sums of independentrandom variables, Poisson processes, Markov chainsand processes, and renewal theory. Assuming only a backgroundin calculus, this outstanding text includes an introductionto basic stochastic processes.Reprint of the Prentice-Hall Publishers, Englewood Cliffs,New Jersey, 1975 edition.

An Introduction to Stochastic Modeling Book
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An Introduction to Stochastic Modeling

  • Author : Howard M. Taylor
  • Publisher : Gulf Professional Publishing
  • Release Date : 1998-02-06
  • Genre: Mathematics
  • Pages : 652
  • ISBN 10 : 0126848874
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Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Third Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems. Realistic applications from a variety of disciplines integrated throughout the text Plentiful, updated and more rigorous problems, including computer "challenges" Revised end-of-chapter exercises sets-in all, 250 exercises with answers New chapter on Brownian motion and related processes Additional sections on Matingales and Poisson process

An Introduction to Order Statistics Book

An Introduction to Order Statistics

  • Author : Mohammad Ahsanullah
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-03-13
  • Genre: Mathematics
  • Pages : 244
  • ISBN 10 : 9789491216831
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This book presents the theory of order statistics in a way, such that beginners can get easily acquainted with the very basis of the theory without having to work through heavily involved techniques. At the same time more experienced readers can check their level of understanding and polish their knowledge with certain details. This is achieved by, on the one hand, stating the basic formulae and providing many useful examples to illustrate the theoretical statements, while on the other hand an upgraded list of references will make it easier to gain insight into more specialized results. Thus this book is suitable for a readership working in statistics, actuarial mathematics, reliability engineering, meteorology, hydrology, business economics, sports analysis and many more.

Introduction to Stochastic Models Book

Introduction to Stochastic Models

  • Author : Roe Goodman
  • Publisher : Courier Corporation
  • Release Date : 2006-01-01
  • Genre: Mathematics
  • Pages : 370
  • ISBN 10 : 9780486450377
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Newly revised by the author, this undergraduate-level text introduces the mathematical theory of probability and stochastic processes. Using both computer simulations and mathematical models of random events, it comprises numerous applications to the physical and biological sciences, engineering, and computer science. Subjects include sample spaces, probabilities distributions and expectations of random variables, conditional expectations, Markov chains, and the Poisson process. Additional topics encompass continuous-time stochastic processes, birth and death processes, steady-state probabilities, general queuing systems, and renewal processes. Each section features worked examples, and exercises appear at the end of each chapter, with numerical solutions at the back of the book. Suggestions for further reading in stochastic processes, simulation, and various applications also appear at the end.

Introduction to Stochastic Processes with R Book

Introduction to Stochastic Processes with R

  • Author : Robert P. Dobrow
  • Publisher : John Wiley & Sons
  • Release Date : 2016-03-07
  • Genre: Mathematics
  • Pages : 503
  • ISBN 10 : 9781118740651
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An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations. Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features: More than 200 examples and 600 end-of-chapter exercises A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black–Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus Introductions to mathematics as needed in order to suit readers at many mathematical levels A companion web site that includes relevant data files as well as all R code and scripts used throughout the book Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

Introduction to Stochastic Processes Book

Introduction to Stochastic Processes

  • Author : Paul G. Hoel
  • Publisher : Waveland Press
  • Release Date : 1986-12-01
  • Genre: Mathematics
  • Pages : 203
  • ISBN 10 : 9781478608998
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An excellent introduction for computer scientists and electrical and electronics engineers who would like to have a good, basic understanding of stochastic processes! This clearly written book responds to the increasing interest in the study of systems that vary in time in a random manner. It presents an introductory account of some of the important topics in the theory of the mathematical models of such systems. The selected topics are conceptually interesting and have fruitful application in various branches of science and technology.

Stochastic Comparisons with Applications Book

Stochastic Comparisons with Applications

  • Author : Subhash C. Kochar
  • Publisher : Springer Nature
  • Release Date : 2022-10-22
  • Genre: Mathematics
  • Pages : 280
  • ISBN 10 : 9783031121043
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This book emphasizes the use of stochastic orders as motivational tools for developing new statistical procedures. Stochastic orders have found useful applications in many disciplines, including reliability theory, survival analysis, risk theory, finance, nonparametric methods, economics and actuarial science. Written by a statistician, this volume clarifies the connection between stochastic orders and nonparametric methods. The importance of order statistics and spacings is well recognized. Classically, they mainly focus on the case when the observations are independent and identically distributed, however, several new developments have extended the comparison of order statistics to the case of non-identically distributed or non-independent observations. In addition to giving a detailed discussion of various topics in the general area of stochastic orders, a substantial part of the book is devoted to recent research on stochastic comparisons of order statistics and spacings, including a long chapter on dependence among them. The book will be useful for graduate students and researchers in statistics, economics, actuarial science and other related disciplines. In particular, with close to 300 references, it will be a valuable resource for reliability theorists, applied probabilists and statisticians. Readers are expected to have taken a first-year graduate level course in mathematical statistics or in applied probability.

Combining Soft Computing and Statistical Methods in Data Analysis Book

Combining Soft Computing and Statistical Methods in Data Analysis

  • Author : Christian Borgelt
  • Publisher : Springer Science & Business Media
  • Release Date : 2010-10-12
  • Genre: Technology & Engineering
  • Pages : 644
  • ISBN 10 : 9783642147463
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Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.

An Introduction to Stochastic Processes Book

An Introduction to Stochastic Processes

  • Author : M. S. Bartlett
  • Publisher : CUP Archive
  • Release Date : 1978
  • Genre: Mathematics
  • Pages : 412
  • ISBN 10 : 0521215854
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Random sequences; Processes in continuous time; Miscellaneous statistical applications; Limiting stochastic operations; Stationary processes; Prediction and communication theory; The statistical analysis of stochastic processes; Correlation analysis of time-series.

Introduction to Stochastic Dynamic Programming Book

Introduction to Stochastic Dynamic Programming

  • Author : Sheldon M. Ross
  • Publisher : Academic Press
  • Release Date : 2014-07-10
  • Genre: Mathematics
  • Pages : 178
  • ISBN 10 : 9781483269092
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Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist—providing counterexamples where appropriate—and then presents methods for obtaining such policies when they do. In addition, general areas of application are presented. The final two chapters are concerned with more specialized models. These include stochastic scheduling models and a type of process known as a multiproject bandit. The mathematical prerequisites for this text are relatively few. No prior knowledge of dynamic programming is assumed and only a moderate familiarity with probability— including the use of conditional expectation—is necessary.

Stochastic Processes with Applications Book

Stochastic Processes with Applications

  • Author : Antonio Di Crescenzo
  • Publisher : MDPI
  • Release Date : 2019-11-28
  • Genre: Mathematics
  • Pages : 284
  • ISBN 10 : 9783039217281
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Stochastic processes have wide relevance in mathematics both for theoretical aspects and for their numerous real-world applications in various domains. They represent a very active research field which is attracting the growing interest of scientists from a range of disciplines. This Special Issue aims to present a collection of current contributions concerning various topics related to stochastic processes and their applications. In particular, the focus here is on applications of stochastic processes as models of dynamic phenomena in research areas certain to be of interest, such as economics, statistical physics, queuing theory, biology, theoretical neurobiology, and reliability theory. Various contributions dealing with theoretical issues on stochastic processes are also included.

Stochastic Ordering and Dependence in Applied Probability Book

Stochastic Ordering and Dependence in Applied Probability

  • Author : R. Szekli
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Genre: Mathematics
  • Pages : 194
  • ISBN 10 : 9781461225287
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This book is an introductionary course in stochastic ordering and dependence in the field of applied probability for readers with some background in mathematics. It is based on lectures and senlinars I have been giving for students at Mathematical Institute of Wroclaw University, and on a graduate course a.t Industrial Engineering Department of Texas A&M University, College Station, and addressed to a reader willing to use for example Lebesgue measure, conditional expectations with respect to sigma fields, martingales, or compensators as a common language in this field. In Chapter 1 a selection of one dimensional orderings is presented together with applications in the theory of queues, some parts of this selection are based on the recent literature (not older than five years). In Chapter 2 the material is centered around the strong stochastic ordering in many dimen sional spaces and functional spaces. Necessary facts about conditioning, Markov processes an"d point processes are introduced together with some classical results such as the product formula and Poissonian departure theorem for Jackson networks, or monotonicity results for some re newal processes, then results on stochastic ordering of networks, re~~ment policies and single server queues connected with Markov renewal processes are given. Chapter 3 is devoted to dependence and relations between dependence and ordering, exem plified by results on queueing networks and point processes among others.