A Graduate Course in Probability:

Probability and Mathematical Statistics: A Series of Monographs and Textbooks: A Graduate Course in Probability presents some of the basic theorems of analytic probability theory in a cohesive manner.This book discusses the probability spaces and distributions, stochastic independence, basic limitin...

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Bibliographic Details
Main Author: Tucker, Howard G. (Author)
Format: Electronic eBook
Language:English
Published: Saint Louis Elsevier Science 2014
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Online Access:FAW01
Summary:Probability and Mathematical Statistics: A Series of Monographs and Textbooks: A Graduate Course in Probability presents some of the basic theorems of analytic probability theory in a cohesive manner.This book discusses the probability spaces and distributions, stochastic independence, basic limiting operations, and strong limit theorems for independent random variables. The central limit theorem, conditional expectation and martingale theory, and Brownian motion are also elaborated. The prerequisite for this text is knowledge of real analysis or measure theory, particularly the Lebesgue dominated convergence theorem, Fubini's theorem, Radon-Nikodym theorem, Egorov's theorem, monotone convergence theorem, and theorem on unique extension of a sigma-finite measure from an algebra to the sigma-algebra generated by it.This publication is suitable for a one-year graduate course in probability given in a mathematics program and preferably for students in their second year of graduate work
Item Description:Description based on publisher supplied metadata and other sources
Physical Description:1 online resource (288 pages)
ISBN:9781483220505
9780127026466

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