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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1. Verfasser: Tucker, Howard G. (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Saint Louis Elsevier Science 2014
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Online-Zugang:FAW01
Zusammenfassung: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
Beschreibung:Description based on publisher supplied metadata and other sources
Beschreibung:1 online resource (288 pages)
ISBN:9781483220505
9780127026466

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