About this product

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-103030618706

ISBN-139783030618704

eBay Product ID (ePID)25050386543

Product Key Features

Number of PagesXii, 946 Pages

Publication NameFoundations of Modern Probability

LanguageEnglish

Publication Year2021

SubjectProbability & Statistics / General

TypeTextbook

AuthorOlav Kallenberg

Subject AreaMathematics

SeriesProbability Theory and Stochastic Modelling Ser.

FormatHardcover

Dimensions

Item Weight62.8 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Edition Number3

Dewey Edition21

Reviews"The book under review is the magnum opus of a brilliant scholar of probability. ... An important feature of the book ... is the writing style. ... The choice of topics is excellent, some of which are not covered elsewhere. This book would make an outstanding text for graduate courses in measure theoretic probability, and for graduate students and faculty doing research in probability. The book is a delight to read. Highly recommended." (Myron Hlynka, Mathematical Reviews, April, 2022)

Series Volume Number99

Number of Volumes2 vols.

IllustratedYes

Dewey Decimal519.2

Table Of ContentIntroduction and Reading Guide.- I.Measure Theoretic Prerequisites: 1.Sets and functions, measures and integration.- 2.Measure extension and decomposition.- 3.Kernels, disintegration, and invariance.- II.Some Classical Probability Theory: 4.Processes, distributions, and independence.- 5.Random sequences, series, and averages.- 6.Gaussian and Poisson convergence.- 7.Infinite divisibility and general null-arrays.- III.Conditioning and Martingales: 8.Conditioning and disintegration.- 9.Optional times and martingales.- 10.Predictability and compensation.- IV.Markovian and Related Structures: 11.Markov properties and discrete-time chains.- 12.Random walks and renewal processes.- 13.Jump-type chains and branching processes.- V.Some Fundamental Processes: 14.Gaussian processes and Brownian motion.- 15.Poisson and related processes.- 16.Independent-increment and Lévy processes.- 17.Feller processes and semi-groups.- VI.Stochastic Calculus and Applications: 18.Itô integration and quadratic variation.- 19.Continuous martingales and Brownian motion.- 20.Semi-martingales and stochastic integration.- 21.Malliavin calculus.- VII.Convergence and Approximation: 22.Skorohod embedding and functional convergence.- 23.Convergence in distribution.- 24.Large deviations.- VIII.Stationarity, Symmetry and Invariance: 25.Stationary processes and ergodic theorems.- 26.Ergodic properties of Markov processes.- 27.Symmetric distributions and predictable maps.- 28.Multi-variate arrays and symmetries.- IX.Random Sets and Measures: 29.Local time, excursions, and additive functionals.- 30.Random mesures, smoothing and scattering.- 31.Palm and Gibbs kernels, local approximation.- X.SDEs, Diffusions, and Potential Theory: 32.Stochastic equations and martingale problems.- 33.One-dimensional SDEs and diffusions.- 34.PDE connections and potential theory.- 35.Stochasticdifferential geometry.- Appendices.- 1.Measurable maps.- 2.General topology.- 3.Linear spaces.- 4.Linear operators.- 5.Function and measure spaces.- 6.Classes and spaces of sets,- 7.Differential geometry.- Notes and References.- Bibliography.- Indices: Authors.- Topics.- Symbols.

SynopsisThis new, thoroughly revised and expanded 3rd edition of a classic gives a comprehensive coverage of modern probability in a single book. It is a truly modern text, providing not only classical results but also material that will be important for future research. Much has been added to the previous edition, including eight entirely new chapters on subjects like random measures, Malliavin calculus, multivariate arrays, and stochastic differential geometry. Apart from important improvements and revisions, some of the earlier chapters have been entirely rewritten. To help the reader, the material has been grouped together into ten major areas, each arguably indispensable to any serious graduate student and researcher, regardless of their specialization. Each chapter is largely self-contained and includes plenty of exercises, making the book ideal for self-study and for designing graduate-level courses and seminars in different areas and at different levels. Extensive notes and a detailed bibliography make it easy to go beyond the presented material if desired. From the reviews of the first edition: "...readers are likely to regard the book as an ideal reference. Indeed the monograph has the potential to become a (possibly even "the") major reference book on large parts of probability theory for the next decade or more." M. Scheutzow, zbMATH "...great edifice of material, clearly and ingeniously presented, without any non-mathematical distractions. Readers ... are in very capable hands." F. B. Knight, Mathemtical Reviews "... this is precisely what Professor Kallenberg has attempted ... and he has accomplished it brilliantly... It is astonishing that a single volume of just over five hundred pages could contain so much material presented with complete rigor and still be at least formally self-contained..." R.K. Getoor, Metrika From the reviews of the second edition: "This ... edition presents ... more material in the concise and elegant style of the former edition which by now has become a highly praised standard reference book for many areas of probability theory." M. Reiß, zbMATH "...the ... monograph is a modern classic in probability theory... ...every ... expert in one of the various topics covered by this monograph will reconsider his own point of view and gain deeper insight into his subject." Klaus D. Schmidt, Mathematical Reviews, About the first edition: To sum it up, one can perhaps see a distinction among advanced probability books into those which are original and path-breaking in content, such as Levy's and Doob's well-known examples, and those which aim primarily to assimilate known material, such as Loeve's and more recently Rogers and Williams'. Seen in this light, Kallenberg's present book would have to qualify as the assimilation of probability par excellence. It is a great edifice of material, clearly and ingeniously presented, without any non-mathematical distractions. Readers wishing to venture into it may do so with confidence that they are in very capable hands. - Mathematical Reviews This new edition contains four new chapters as well as numerous improvements throughout the text. There are new chapters on measure Theory-key results, ergodic properties of Markov processes and large deviations.

LC Classification NumberQA273.A1-274.9