Conditional Measures and Applications
Autor M. M. Raoen Limba Engleză Hardback – 25 mai 2005
Conditional Measures and Applications, Second Edition clearly elucidates the subject, from fundamental principles to abstract analysis. The author illustrates the computational difficulties in evaluating conditional probabilities in nondiscrete cases with numerous examples, demonstrates applications to Markov processes, martingales, potential theory, and Reynolds operators as well as sufficiency in statistics, and clarifies ideas in modern noncommutative probability structures through conditioning in general structures, including parts of operator algebras and "free" random variables. He also discusses existence and construction problems from the Bishop-Brouwer constructive analysis point of view.
With open problems in every chapter and links to other areas of mathematics, this invaluable second edition offers complete coverage of conditional probability and expectation and their structural analysis, from simple to advanced abstract levels, for both novices and seasoned mathematicians.
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Specificații
ISBN-13: 9781574445930
ISBN-10: 1574445936
Pagini: 506
Dimensiuni: 152 x 229 x 32 mm
Greutate: 0.79 kg
Ediția:Revizuită
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 1574445936
Pagini: 506
Dimensiuni: 152 x 229 x 32 mm
Greutate: 0.79 kg
Ediția:Revizuită
Editura: CRC Press
Colecția Chapman and Hall/CRC
Public țintă
ProfessionalCuprins
Preface to the Second Edition. Preface to the First Edition. The Concept of Conditioning. The Kolmogorov Formulation and Its Properties. Computational Problems Associated with Conditioning. An Axiomatic Approach to Conditional Probability. Regularity of Conditional Measures. Sufficiency. Abstraction of Kolmogorov's Formulation. Products of Conditional Measures. Applications to Martingales and Markov Processes. Applications to Modern Analysis. Conditioning in General Structures. References. Notations. Author Index. Subject Index.
Descriere
The second edition of this authoritative text offers an in-depth treatment of all aspects of conditional expectations and probability measures and their structural analysis. However, what makes this the definitive reference on conditional measures is the author's keen ability to link theory with practical applications. The author covers applications in sufficiency, Markov processes, and martingales. He also illustrates the difficulties in calculating conditional expectations for continuous multivariate distributions and methods for correct solutions in such cases. Each chapter concludes with several open-ended problems that reinforce principles and promote practical problem solving.