Measure Theory and Probability Theory

Krishna B. Athreya, Soumen N. Lahiri - Collection Springer texts in statistics

618 pages, parution le 01/07/2006

Ajouter à une liste

Indisponible

Résumé

This is a graduate level textbook on measure theory and probability theory. It presents the main concepts and results in measure theory and probability theory in a simple and easy-to-understand way. It further provides heuristic explanations behind the theory to help students see the big picture. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics. Prerequisites are kept to the minimal level and the book is intended primarily for first year Ph.D. students in mathematics and statistics.

Written for:

Graduate students, researchers

Sommaire

Measures and integration: an informal introduction
Measures
Integration
L[superscript p]-spaces
Differentiation
Product measures, convolutions, and transforms
Probability spaces
Independence
Laws of large numbers
Convergence in distribution
Characteristic functions
Central limit theorems
Conditional expectation and conditional probability
Discrete parameter martingales
Markov chains and MCMC
Stochastic processes
Limit theorems for dependent processes
The bootstrap
Branching processes
A: Advanced calculus: a review

Voir tout

Replier

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Krishna B. Athreya, Soumen N. Lahiri
Collection	Springer texts in statistics
Parution	01/07/2006
Nb. de pages	618
Couverture	Relié
Intérieur	Noir et Blanc
EAN13	9780387329031
ISBN13	978-0-387-32903-1