Books in Probability theory and stochastic processes

31-40 of 106 results in All results

Semi-Markov Models

• 1st Edition
• February 2, 2015
• Yuriy E Obzherin + 1 more
• English
• Paperback 978-0-12-802212-2

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• eBook 978-0-12-802486-7

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Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and utilizing the method of asymptotic phase enlargement developed by V.S. Korolyuk and A.F. Turbin. The work then explores semi-Markov models of latent failures control in two-component systems. Building on these results, solutions are provided for the problems of optimal periodicity of control execution. Finally, the book presents a comparative analysis of analytical and imitational modeling of some one- and two-component systems, before discussing practical applications of the results

An Introduction to Probability and Statistical Inference

• 2nd Edition
• September 25, 2014
• George G. Roussas
• English
• Hardback 978-0-12-800114-1

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• eBook 978-0-12-800437-1

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An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help them obtain the best solution to a posed question or situation. It provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. This text contains an enhanced number of exercises and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities. Reorganized material is included in the statistical portion of the book to ensure continuity and enhance understanding. Each section includes relevant proofs where appropriate, followed by exercises with useful clues to their solutions. Furthermore, there are brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises are available to instructors in an Answers Manual. This text will appeal to advanced undergraduate and graduate students, as well as researchers and practitioners in engineering, business, social sciences or agriculture.

Introduction to Probability and Statistics for Engineers and Scientists

• 5th Edition
• August 14, 2014
• Sheldon M. Ross
• English
• eBook 978-0-12-394842-7

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Introduction to Probability and Statistics for Engineers and Scientists, Fifth Edition is a proven text reference that provides a superior introduction to applied probability and statistics for engineering or science majors. The book lays emphasis in the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data from actual studies across life science, engineering, computing and business are incorporated in a wide variety of exercises and examples throughout the text. These examples and exercises are combined with updated problem sets and applications to connect probability theory to everyday statistical problems and situations. The book also contains end of chapter review material that highlights key ideas as well as the risks associated with practical application of the material. Furthermore, there are new additions to proofs in the estimation section as well as new coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions. This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational content and application to these fields.

Order Statistics & Inference

• 1st Edition
• June 28, 2014
• Narayanaswamy Balakrishnan + 1 more
• English
• eBook 978-1-4832-9749-1

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The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A complete, comprehensive bibliography is included so the book can be used both aas a text and reference.

Statistical Methods in Longitudinal Research

• 1st Edition
• Volume 1
• June 28, 2014
• Alexander von Eye
• English
• eBook 978-1-4832-9795-8

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These edited volumes present new statistical methods in a way that bridges the gap between theoretical and applied statistics. The volumes cover general problems and issues and more specific topics concerning the structuring of change, the analysis of time series, and the analysis of categorical longitudinal data. The book targets students of development and change in a variety of fields - psychology, sociology, anthropology, education, medicine, psychiatry, economics, behavioural sciences, developmental psychology, ecology, plant physiology, and biometry - with basic training in statistics and computing.

Stochastic Differential Equations and Diffusion Processes

• 2nd Edition
• Volume 24
• June 28, 2014
• N. Ikeda + 1 more
• English
• eBook 978-1-4832-9615-9

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Being a systematic treatment of the modern theory of stochastic integrals and stochastic differential equations, the theory is developed within the martingale framework, which was developed by J.L. Doob and which plays an indispensable role in the modern theory of stochastic analysis.A considerable number of corrections and improvements have been made for the second edition of this classic work. In particular, major and substantial changes are in Chapter III and Chapter V where the sections treating excursions of Brownian Motion and the Malliavin Calculus have been expanded and refined. Sections discussing complex (conformal) martingales and Kahler diffusions have been added.

Mathematical Methods of Reliability Theory

• 1st Edition
• June 20, 2014
• B. V. Gnedenko + 2 more
• Z. W. Birnbaum + 1 more
• English
• eBook 978-1-4832-6351-9

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Mathematical Methods of Reliability Theory discusses fundamental concepts of probability theory, mathematical statistics, and an exposition of the relationships among the fundamental quantitative characteristics encountered in the theory. The book deals with the set-theoretic approach to reliability theory and the central concepts of set theory to the phenomena. It also presents methods of finding estimates for reliability parameters based on observations and methods of testing reliability hypotheses. Based on mathematical statistics, the book also explains formulation of some selected results. It presents a method that increases the reliability of manufactured articles—redundancy. An important part of product quality control is the standards of acceptance-sampling plans which require simplicity, wide content for flexibility, comprehensive characteristics, and variability. The book also tackles economical and rational methods of sampling inspections, highlighting the need for a correct evaluation of environmental conditions—the factors which predetermine the choice of the inspection method. The book then explains how to estimate the efficiency of the operation of the sampling plan after its selection. The book can be helpful for engineers, mathematicians, economists, or industrial managers, as well as for other professionals who work in the technological, political, research, structural, and physico-chemical areas.

Fundamentals of Applied Probability and Random Processes

• 2nd Edition
• June 13, 2014
• Oliver Ibe
• English
• Hardback 978-0-12-800852-2

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• eBook 978-0-12-801035-8

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The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study.

An Introduction to Probability and Mathematical Statistics

• 1st Edition
• May 12, 2014
• Howard G. Tucker
• Ralph P. Boas
• English
• eBook 978-1-4832-2514-2

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An Introduction to Probability and Mathematical Statistics provides information pertinent to the fundamental aspects of probability and mathematical statistics. This book covers a variety of topics, including random variables, probability distributions, discrete distributions, and point estimation. Organized into 13 chapters, this book begins with an overview of the definition of function. This text then examines the notion of conditional or relative probability. Other chapters consider Cochran's theorem, which is of extreme importance in that part of statistical inference known as analysis of variance. This book discusses as well the fundamental principles of testing statistical hypotheses by providing the reader with an idea of the basic problem and its relation to practice. The final chapter deals with the problem of estimation and the Neyman theory of confidence intervals. This book is a valuable resource for undergraduate university students who are majoring in mathematics. Students who are majoring in physics and who are inclined toward abstract mathematics will also find this book useful.

Theory of Markov Processes

• 1st Edition
• May 12, 2014
• E. B. Dynkin
• T. Köváry
• English
• eBook 978-1-4832-2610-1

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Theory of Markov Processes provides information pertinent to the logical foundations of the theory of Markov random processes. This book discusses the properties of the trajectories of Markov processes and their infinitesimal operators. Organized into six chapters, this book begins with an overview of the necessary concepts and theorems from measure theory. This text then provides a general definition of Markov process and investigates the operations that make possible an inspection of the class of Markov processes corresponding to a given transition function. Other chapters consider the more complicated operation of generating a subprocess. This book discusses as well the construction of Markov processes with given transition functions. The final chapter deals with the conditions to be imposed on the transition function so that among the Markov processes corresponding to this function, there should be at least one. This book is a valuable resource for mathematicians, students, and research workers.