Probability Theory An Analytic View
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| Author | : Daniel W. Stroock |
| Publisher | : Cambridge University Press |
| Total Pages | : 550 |
| Release | : 2010-12-31 |
| Genre | : Mathematics |
| ISBN | : 1139494619 |
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.
| Author | : Daniel W. Stroock |
| Publisher | : Cambridge University Press |
| Total Pages | : 0 |
| Release | : 2024-12-31 |
| Genre | : Mathematics |
| ISBN | : 9781009549004 |
The third edition of this highly regarded text provides a rigorous, yet entertaining, introduction to probability theory and the analytic ideas and tools on which the modern theory relies. The main changes are the inclusion of the Gaussian isoperimetric inequality plus many improvements and clarifications throughout the text. With more than 750 exercises, it is ideal for first-year graduate students with a good grasp of undergraduate probability theory and analysis. Starting with results about independent random variables, the author introduces weak convergence of measures and its application to the central limit theorem, and infinitely divisible laws and their associated stochastic processes. Conditional expectation and martingales follow before the context shifts to infinite dimensions, where Gaussian measures and weak convergence of measures are studied. The remainder is devoted to the mutually beneficial connection between probability theory and partial differential equations, culminating in an explanation of the relationship of Brownian motion to classical potential theory.
| Author | : Daniel W. Stroock |
| Publisher | : Cambridge University Press |
| Total Pages | : 558 |
| Release | : 1999 |
| Genre | : Mathematics |
| ISBN | : 9780521663496 |
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.
| Author | : G. Tenenbaum |
| Publisher | : Cambridge University Press |
| Total Pages | : 180 |
| Release | : 1995-06-30 |
| Genre | : Mathematics |
| ISBN | : 9780521412612 |
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.
| Author | : Daniel W. Stroock |
| Publisher | : American Mathematical Soc. |
| Total Pages | : 299 |
| Release | : 2013-07-05 |
| Genre | : Mathematics |
| ISBN | : 1470409070 |
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.
| Author | : Rick Durrett |
| Publisher | : Cambridge University Press |
| Total Pages | : |
| Release | : 2010-08-30 |
| Genre | : Mathematics |
| ISBN | : 113949113X |
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.
| Author | : R. M. Dudley |
| Publisher | : Cambridge University Press |
| Total Pages | : 570 |
| Release | : 2002-10-14 |
| Genre | : Mathematics |
| ISBN | : 9780521007542 |
This classic text offers a clear exposition of modern probability theory.
| Author | : Philippe Flajolet |
| Publisher | : Cambridge University Press |
| Total Pages | : 825 |
| Release | : 2009-01-15 |
| Genre | : Mathematics |
| ISBN | : 1139477161 |
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.
| Author | : Edward Nelson |
| Publisher | : Princeton University Press |
| Total Pages | : 112 |
| Release | : 1987 |
| Genre | : Mathematics |
| ISBN | : 9780691084749 |
Using only the very elementary framework of finite probability spaces, this book treats a number of topics in the modern theory of stochastic processes. This is made possible by using a small amount of Abraham Robinson's nonstandard analysis and not attempting to convert the results into conventional form.
| Author | : James A. Mingo |
| Publisher | : Springer |
| Total Pages | : 343 |
| Release | : 2017-06-24 |
| Genre | : Mathematics |
| ISBN | : 1493969420 |
This volume opens the world of free probability to a wide variety of readers. From its roots in the theory of operator algebras, free probability has intertwined with non-crossing partitions, random matrices, applications in wireless communications, representation theory of large groups, quantum groups, the invariant subspace problem, large deviations, subfactors, and beyond. This book puts a special emphasis on the relation of free probability to random matrices, but also touches upon the operator algebraic, combinatorial, and analytic aspects of the theory. The book serves as a combination textbook/research monograph, with self-contained chapters, exercises scattered throughout the text, and coverage of important ongoing progress of the theory. It will appeal to graduate students and all mathematicians interested in random matrices and free probability from the point of view of operator algebras, combinatorics, analytic functions, or applications in engineering and statistical physics.
