Probability Theory

Probability Theory PDF

Author: Daniel W. Stroock

Publisher: Cambridge University Press

Published: 2010-12-31

Total Pages: 550

ISBN-13: 1139494619

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This second edition of Daniel W. Stroock's text is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability theory and a sound grounding in analysis. It is intended to provide readers with an introduction to probability theory and the analytic ideas and tools on which the modern theory relies. It includes more than 750 exercises. Much of the content has undergone significant revision. In particular, the treatment of Levy processes has been rewritten, and a detailed account of Gaussian measures on a Banach space is given.

Probability Theory: an Analytic View

Probability Theory: an Analytic View PDF

Author: Daniel W. Stroock

Publisher:

Published: 1993

Total Pages: 512

ISBN-13:

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This section also explores the connection between martingales and various aspects of classical analysis, and the connections between Wiener's measure and classical potential theory. Although the book is primarily intended for students and practitioners of probability theory and analysis, it will also be a valuable reference for those in fields as diverse as physics, engineering, and economics.

Probability Theory, an Analytic View

Probability Theory, an Analytic View PDF

Author: Daniel W. Stroock

Publisher: Cambridge University Press

Published: 1999

Total Pages: 558

ISBN-13: 9780521663496

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This revised edition is suitable for a first-year graduate course on probability theory. It is intended for students with a good grasp of introductory, undergraduate probability and is a reasonably sophisticated introduction to modern analysis for those who want to learn what these two topics have to say about each other. The first part of the book deals with independent random variables, Central Limit phenomena, the general theory of weak convergence and several of its applications, as well as elements of both the Gaussian and Markovian theory of measures on function space. The introduction of conditional expectation values is postponed until the second part of the book where it is applied to the study of martingales. This section also explores the connection between martingales and various aspects of classical analysis and the connections between Wiener's measure and classical potential theory.

Probability Theory, an Analytic View

Probability Theory, an Analytic View PDF

Author: Daniel W. Stroock

Publisher: Cambridge University Press

Published: 2000-01-28

Total Pages: 556

ISBN-13: 9780521663496

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This revised edition of Daniel W. Stroock's classic text is suitable for a first-year graduate course on probability theory. By modern standards the topics treated are classical and the techniques used far-ranging: Dr. Stroock does not approach the subject as a monolithic structure resting on a few basic principles. The first part of the book deals with independent random variables, Central Limit phenomena, the general theory of weak convergence and several of its applications, as well as elements of both the Gaussian and Markovian theory of measures on function space. Stroock covers conditional expectation values in the second half where he applies them to the study of martingales. He also explores the connection between martingales and various aspects of classical analysis and the connections between Wiener's measure and classical potential theory. Student prerequisites are a good grasp of introductory, undergraduate probability theory and a reasonably sophisticated knowledge of analysis.

Markov Processes from K. Itô's Perspective

Markov Processes from K. Itô's Perspective PDF

Author: Daniel W. Stroock

Publisher: Princeton University Press

Published: 2003-05-26

Total Pages: 288

ISBN-13: 0691115435

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Kiyosi Itô's greatest contribution to probability theory may be his introduction of stochastic differential equations to explain the Kolmogorov-Feller theory of Markov processes. Starting with the geometric ideas that guided him, this book gives an account of Itô's program. The modern theory of Markov processes was initiated by A. N. Kolmogorov. However, Kolmogorov's approach was too analytic to reveal the probabilistic foundations on which it rests. In particular, it hides the central role played by the simplest Markov processes: those with independent, identically distributed increments. To remedy this defect, Itô interpreted Kolmogorov's famous forward equation as an equation that describes the integral curve of a vector field on the space of probability measures. Thus, in order to show how Itô's thinking leads to his theory of stochastic integral equations, Stroock begins with an account of integral curves on the space of probability measures and then arrives at stochastic integral equations when he moves to a pathspace setting. In the first half of the book, everything is done in the context of general independent increment processes and without explicit use of Itô's stochastic integral calculus. In the second half, the author provides a systematic development of Itô's theory of stochastic integration: first for Brownian motion and then for continuous martingales. The final chapter presents Stratonovich's variation on Itô's theme and ends with an application to the characterization of the paths on which a diffusion is supported. The book should be accessible to readers who have mastered the essentials of modern probability theory and should provide such readers with a reasonably thorough introduction to continuous-time, stochastic processes.

Mathematics of Probability

Mathematics of Probability PDF

Author: Daniel W. Stroock

Publisher: American Mathematical Soc.

Published: 2013-07-05

Total Pages: 299

ISBN-13: 1470409070

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This book covers the basics of modern probability theory. It begins with probability theory on finite and countable sample spaces and then passes from there to a concise course on measure theory, which is followed by some initial applications to probability theory, including independence and conditional expectations. The second half of the book deals with Gaussian random variables, with Markov chains, with a few continuous parameter processes, including Brownian motion, and, finally, with martingales, both discrete and continuous parameter ones. The book is a self-contained introduction to probability theory and the measure theory required to study it.

Analytic Combinatorics

Analytic Combinatorics PDF

Author: Philippe Flajolet

Publisher: Cambridge University Press

Published: 2009-01-15

Total Pages: 825

ISBN-13: 1139477161

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Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanced undergraduate or a graduate course, or for self-study.

Introduction to Analytic and Probabilistic Number Theory

Introduction to Analytic and Probabilistic Number Theory PDF

Author: G. Tenenbaum

Publisher: Cambridge University Press

Published: 1995-06-30

Total Pages: 180

ISBN-13: 9780521412612

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This is a self-contained introduction to analytic methods in number theory, assuming on the part of the reader only what is typically learned in a standard undergraduate degree course. It offers to students and those beginning research a systematic and consistent account of the subject but will also be a convenient resource and reference for more experienced mathematicians. These aspects are aided by the inclusion at the end of each chapter a section of bibliographic notes and detailed exercises.

Probability theory an analytic view

Probability theory an analytic view PDF

Author:

Publisher:

Published: 2016

Total Pages: 545

ISBN-13: 9787519205348

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本书通过重点介绍现代概率论的分析思路与其所用的分析工具之间的相辅相成的关系,相当详细地介绍了现代概率论.第2版中的练习题超过750道,并且对Levy过程,大偏差理论,Banach空间上的Gauss测度,Wiener测度与偏微分方程的关系等添加了许多新的素材.

Probability

Probability PDF

Author: Rick Durrett

Publisher: Cambridge University Press

Published: 2010-08-30

Total Pages:

ISBN-13: 113949113X

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This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The fourth edition begins with a short chapter on measure theory to orient readers new to the subject.