Functional Analysis for Probability and Stochastic Processes ICM Edition
Author: Bobrowski
Publisher:
Published: 2010-07-23
Total Pages:
ISBN-13: 9780521169912
DOWNLOAD EBOOK →Lanterna Rally
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Functional Analysis for Probability and Stochastic Processes
Author: Adam Bobrowski
Publisher: Cambridge University Press
Published: 2005-08-11
Total Pages: 407
ISBN-13: 1139443887
DOWNLOAD EBOOK →This text is designed both for students of probability and stochastic processes, and for students of functional analysis. For the reader not familiar with functional analysis a detailed introduction to necessary notions and facts is provided. However, this is not a straight textbook in functional analysis; rather, it presents some chosen parts of functional analysis that can help understand ideas from probability and stochastic processes. The subjects range from basic Hilbert and Banach spaces, through weak topologies and Banach algebras, to the theory of semigroups of bounded linear operators. Numerous standard and non-standard examples and exercises make the book suitable as a course textbook or for self-study.
Stochastic Processes and Functional Analysis
Author: Jerome Goldstein
Publisher: CRC Press
Published: 2020-09-23
Total Pages: 300
ISBN-13: 1000148637
DOWNLOAD EBOOK →"Covers the areas of modern analysis and probability theory. Presents a collection of papers given at the Festschrift held in honor of the 65 birthday of M. M. Rao, whose prolific published research includes the well-received Marcel Dekker, Inc. books Theory of Orlicz Spaces and Conditional Measures and Applications. Features previously unpublished research articles by a host of internationally recognized scholars."
Stochastic Processes and Functional Analysis
Author: Randall J. Swift
Publisher: American Mathematical Society
Published: 2021-11-22
Total Pages: 248
ISBN-13: 1470459825
DOWNLOAD EBOOK →This volume contains the proceedings of the AMS Special Session on Celebrating M. M. Rao's Many Mathematical Contributions as he Turns 90 Years Old, held from November 9–10, 2019, at the University of California, Riverside, California. The articles show the effectiveness of abstract analysis for solving fundamental problems of stochastic theory, specifically the use of functional analytic methods for elucidating stochastic processes and their applications. The volume also includes a biography of M. M. Rao and the list of his publications.
Stochastic Processes and Functional Analysis
Author: Alan C. Krinik
Publisher: CRC Press
Published: 2004-03-23
Total Pages: 526
ISBN-13: 9780203913574
DOWNLOAD EBOOK →This extraordinary compilation is an expansion of the recent American Mathematical Society Special Session celebrating M. M. Rao's distinguished career and includes most of the presented papers as well as ancillary contributions from session invitees. This book shows the effectiveness of abstract analysis for solving fundamental problems of stochas
概率论与随机过程中的泛涵分析
Author: Adam Bobrowski
Publisher:
Published: 2005
Total Pages: 393
ISBN-13: 9787040236064
DOWNLOAD EBOOK →本书是作者在Rice大学和Houston大学给研究生授课的讲义基础上写成的。本书在介绍了泛函分析的基本概念(如Banach空间)后,用Hilbert空间泛函的F.Riesz表示定理建立Radon-Nikodym定理,从而引进条件期望的概念。
Stochastic Analysis
Author: Shigeo Kusuoka
Publisher: Springer Nature
Published: 2020-10-20
Total Pages: 218
ISBN-13: 9811588643
DOWNLOAD EBOOK →This book is intended for university seniors and graduate students majoring in probability theory or mathematical finance. In the first chapter, results in probability theory are reviewed. Then, it follows a discussion of discrete-time martingales, continuous time square integrable martingales (particularly, continuous martingales of continuous paths), stochastic integrations with respect to continuous local martingales, and stochastic differential equations driven by Brownian motions. In the final chapter, applications to mathematical finance are given. The preliminary knowledge needed by the reader is linear algebra and measure theory. Rigorous proofs are provided for theorems, propositions, and lemmas. In this book, the definition of conditional expectations is slightly different than what is usually found in other textbooks. For the Doob–Meyer decomposition theorem, only square integrable submartingales are considered, and only elementary facts of the square integrable functions are used in the proof. In stochastic differential equations, the Euler–Maruyama approximation is used mainly to prove the uniqueness of martingale problems and the smoothness of solutions of stochastic differential equations.
Stochastic Processes - Inference Theory
Author: Malempati M. Rao
Publisher: Springer
Published: 2014-11-14
Total Pages: 685
ISBN-13: 3319121723
DOWNLOAD EBOOK →This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Multidimensional Second Order Stochastic Processes (Second Edition)
Author: Yuichiro Kakihara
Publisher: Multivariate Analysis
Published: 2020-09-29
Total Pages: 540
ISBN-13: 9789811211744
DOWNLOAD EBOOK →"Functional analysis methods are used on stochastic processes. Structural analysis of nonstationary and stationary processes are also included. This book is in the intersection of probability theory and analysis"--
Stochastic Processes
Author: Kaddour Najim
Publisher: Elsevier
Published: 2004-07-01
Total Pages: 345
ISBN-13: 008051779X
DOWNLOAD EBOOK →A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab. Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications. * An engineering approach to applied probabilities and statistics * Presents examples related to practical engineering applications, such as reliability, randomness and use of resources* Readers with varying interests and mathematical backgrounds will find this book accessible
