Stationary Stochastic Processes. (MN-8)
Stationary Stochastic Processes. (MN-8)

Author: Takeyuki Hida

Publisher: Princeton University Press

Published: 2015-03-08

Total Pages: 175

ISBN-13: 1400868572

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Encompassing both introductory and more advanced research material, these notes deal with the author's contributions to stochastic processes and focus on Brownian motion processes and its derivative white noise. Originally published in 1970. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Stationary Stochastic Processes for Scientists and Engineers
Stationary Stochastic Processes for Scientists and Engineers

Author: Georg Lindgren

Publisher: CRC Press

Published: 2013-10-11

Total Pages: 316

ISBN-13: 1466586192

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Suitable for a one-semester course, this text teaches students how to use stochastic processes efficiently. Carefully balancing mathematical rigor and ease of exposition, the book provides students with a sufficient understanding of the theory and a practical appreciation of how it is used in real-life situations. Special emphasis is on the interpretation of various statistical models and concepts as well as the types of questions statistical analysis can answer. To enable hands-on practice, MATLAB code is available online.

Essentials of Stochastic Processes
Essentials of Stochastic Processes

Author: Richard Durrett

Publisher: Springer

Published: 2016-11-07

Total Pages: 282

ISBN-13: 3319456148

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Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatment of other topics useful for applications has been expanded. In addition, the ordering of topics has been improved; for example, the difficult subject of martingales is delayed until its usefulness can be applied in the treatment of mathematical finance.

Stationary Stochastic Processes
Stationary Stochastic Processes

Author: Georg Lindgren

Publisher: CRC Press

Published: 2012-10-01

Total Pages: 378

ISBN-13: 1466557796

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Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for stationary processes and fields, including a portion on stationary point processes. Features Presents and illustrates the fundamental correlation and spectral methods for stochastic processes and random fields Explains how the basic theory is used in special applications like detection theory and signal processing, spatial statistics, and reliability Motivates mathematical theory from a statistical model-building viewpoint Introduces a selection of special topics, including extreme value theory, filter theory, long-range dependence, and point processes Provides more than 100 exercises with hints to solutions and selected full solutions This book covers key topics such as ergodicity, crossing problems, and extremes, and opens the doors to a selection of special topics, like extreme value theory, filter theory, long-range dependence, and point processes, and includes many exercises and examples to illustrate the theory. Precise in mathematical details without being pedantic, Stationary Stochastic Processes: Theory and Applications is for the student with some experience with stochastic processes and a desire for deeper understanding without getting bogged down in abstract mathematics.

Stochastic Processes
Stochastic Processes

Author: Narahari Umanath Prabhu

Publisher: World Scientific

Published: 2007

Total Pages: 356

ISBN-13: 9812706267

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Most introductory textbooks on stochastic processes which cover standard topics such as Poisson process, Brownian motion, renewal theory and random walks deal inadequately with their applications. Written in a simple and accessible manner, this book addresses that inadequacy and provides guidelines and tools to study the applications. The coverage includes research developments in Markov property, martingales, regenerative phenomena and Tauberian theorems, and covers measure theory at an elementary level.

Stationary and Related Stochastic Processes
Stationary and Related Stochastic Processes

Author: Harald Cramér

Publisher: Courier Corporation

Published: 2004-11-29

Total Pages: 368

ISBN-13: 0486438279

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This graduate-level text offers a comprehensive account of the general theory of stationary processes, with special emphasis on the properties of sample functions. The text develops the foundations of the general theory of stochastic processes, examines processes with a continuous-time parameter, and applies the general theory to procedures key to the study of stationary processes. 1967 edition.

A First Course in Stochastic Processes
A First Course in Stochastic Processes

Author: Samuel Karlin

Publisher: Gulf Professional Publishing

Published: 1975-04-11

Total Pages: 577

ISBN-13: 0123985528

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Elements of stochastic processes; Markov chains; The basic limit theorem of markov chains and applications; Classical examples of continuous time markov chains; Renewal processes; Martingales; Brownian motion; Branching processes; Stationary processes.

Combinatorial Stochastic Processes
Combinatorial Stochastic Processes

Author: Jim Pitman

Publisher: Springer Science & Business Media

Published: 2006-05-11

Total Pages: 257

ISBN-13: 354030990X

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The purpose of this text is to bring graduate students specializing in probability theory to current research topics at the interface of combinatorics and stochastic processes. There is particular focus on the theory of random combinatorial structures such as partitions, permutations, trees, forests, and mappings, and connections between the asymptotic theory of enumeration of such structures and the theory of stochastic processes like Brownian motion and Poisson processes.

Stochastic Processes and Applications
Stochastic Processes and Applications

Author: Grigorios A. Pavliotis

Publisher: Springer

Published: 2014-11-19

Total Pages: 345

ISBN-13: 1493913239

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This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.