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Probability Theory

A Comprehensive Course
BuchKartoniert, Paperback
638 Seiten
Englisch
Springererschienen am17.09.20132. Aufl.
This second edition of the popular textbook contains a comprehensive course in modern probability theory, covering a wide variety of topics which are not usually found in introductory textbooks, including: * limit theorems for sums of random variables* martingales* percolation* Markov chains and electrical networks* construction of stochastic processes* Poisson point process and infinite divisibility* large deviation principles and statistical physics* Brownian motion* stochastic integral and stochastic differential equations.The theory is developed rigorously and in a self-contained way, with the chapters on measure theory interlaced with the probabilistic chapters in order to display the power of the abstract concepts in probability theory. This second edition has been carefully extended and includes many new features. It contains updated figures (over 50), computer simulations and some difficult proofs have been made more accessible. A wealth of examples and more than 270 exercises as well as biographic details of key mathematicians support and enliven the presentation. It will be of use to students and researchers in mathematics and statistics in physics, computer science, economics and biology.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR85,59
BuchKartoniert, Paperback
EUR35,30
E-BookPDF1 - PDF WatermarkE-Book
EUR60,98
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EUR90,94
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Produkt

KlappentextThis second edition of the popular textbook contains a comprehensive course in modern probability theory, covering a wide variety of topics which are not usually found in introductory textbooks, including: * limit theorems for sums of random variables* martingales* percolation* Markov chains and electrical networks* construction of stochastic processes* Poisson point process and infinite divisibility* large deviation principles and statistical physics* Brownian motion* stochastic integral and stochastic differential equations.The theory is developed rigorously and in a self-contained way, with the chapters on measure theory interlaced with the probabilistic chapters in order to display the power of the abstract concepts in probability theory. This second edition has been carefully extended and includes many new features. It contains updated figures (over 50), computer simulations and some difficult proofs have been made more accessible. A wealth of examples and more than 270 exercises as well as biographic details of key mathematicians support and enliven the presentation. It will be of use to students and researchers in mathematics and statistics in physics, computer science, economics and biology.
ZusammenfassungThis second edition of the popular textbook contains a comprehensive course in modern probability theory. It includes a wealth of examples and more than 270 exercises as well as biographic details of key mathematicians.
Details
ISBN/GTIN978-1-4471-5360-3
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2013
Erscheinungsdatum17.09.2013
Auflage2. Aufl.
Reihen-Nr.Universitext
Seiten638 Seiten
SpracheEnglisch
Gewicht815 g
Illustrationen26 SW-Abb., 20 Farbabb., 1 Tabellen
Artikel-Nr.29034052

Inhalt/Kritik

Inhaltsverzeichnis
Basic Measure Theory.- Independence.- Generating Functions.- The Integral.- Moments and Laws of Large Numbers.- Convergence Theorems.- Lp-Spaces and the Radon-Nikodym Theorem.- Conditional Expectations.- Martingales.- Optional Sampling Theorems.- Martingale Convergence Theorems and Their Applications.- Backwards Martingales and Exchangeability.- Convergence of Measures.- Probability Measures on Product Spaces.- Characteristic Functions and the Central Limit Theorem.- Infinitely Divisible Distributions.- Markov Chains.- Convergence of Markov Chains.- Markov Chains and Electrical Networks.- Ergodic Theory.- Brownian Motion.- Law of the Iterated Logarithm.- Large Deviations.- The Poisson Point Process.- The Ito Integral.- Stochastic Differential Equations.mehr
Kritik
From the reviews of the second edition:

The book under review is a standard graduate textbook in this area of mathematics that collects various classical and modern topics in a friendly volume. the book contains many exercises. It is a very good source for a course in probability theory for advanced undergraduates and first-year graduate students. the book should be useful for a wide range of audiences, including students, instructors, and researchers from all branches of science who are dealing with random phenomena. (Mehdi Hassani, MAA Reviews, May, 2014)
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