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: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Saint Louis
Elsevier Science
2014
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Schlagworte: | |
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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520 | |a 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 | ||
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Datensatz im Suchindex
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any_adam_object | |
author | Tucker, Howard G. |
author_facet | Tucker, Howard G. |
author_role | aut |
author_sort | Tucker, Howard G. |
author_variant | h g t hg hgt |
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dewey-full | 519.2 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.2 |
dewey-search | 519.2 |
dewey-sort | 3519.2 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik |
format | Electronic eBook |
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institution | BVB |
isbn | 9781483220505 9780127026466 |
language | English |
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spelling | Tucker, Howard G. Verfasser aut A Graduate Course in Probability Saint Louis Elsevier Science 2014 © 1967 1 online resource (288 pages) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources 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 Probabilities Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf Wahrscheinlichkeit (DE-588)4137007-7 gnd rswk-swf Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s 1\p DE-604 Wahrscheinlichkeit (DE-588)4137007-7 s 2\p DE-604 Birnbaum, Z. W. Sonstige oth Lukacs, E. Sonstige oth Erscheint auch als Druck-Ausgabe Tucker, Howard G . A Graduate Course in Probability 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Tucker, Howard G. A Graduate Course in Probability Probabilities Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Wahrscheinlichkeit (DE-588)4137007-7 gnd |
subject_GND | (DE-588)4064324-4 (DE-588)4137007-7 |
title | A Graduate Course in Probability |
title_auth | A Graduate Course in Probability |
title_exact_search | A Graduate Course in Probability |
title_full | A Graduate Course in Probability |
title_fullStr | A Graduate Course in Probability |
title_full_unstemmed | A Graduate Course in Probability |
title_short | A Graduate Course in Probability |
title_sort | a graduate course in probability |
topic | Probabilities Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Wahrscheinlichkeit (DE-588)4137007-7 gnd |
topic_facet | Probabilities Wahrscheinlichkeitsrechnung Wahrscheinlichkeit |
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