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Lahiri / Athreya

Measure Theory and Probability Theory

Medium: Buch
ISBN: 978-1-4419-2191-8
Verlag: Springer
Erscheinungstermin: 23.11.2010
Lieferfrist: bis zu 10 Tage

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. It is intended primarily for first year Ph.D. students in mathematics and statistics although mathematically advanced students from engineering and economics would also find the book useful. Prerequisites are kept to the minimal level of an understanding of basic real analysis concepts such as limits, continuity, differentiability, Riemann integration, and convergence of sequences and series. A review of this material is included in the appendix.


Produkteigenschaften


  • Artikelnummer: 9781441921918
  • Medium: Buch
  • ISBN: 978-1-4419-2191-8
  • Verlag: Springer
  • Erscheinungstermin: 23.11.2010
  • Sprache(n): Englisch
  • Auflage: 1. Auflage. Softcover version of original hardcover Auflage 2006
  • Serie: Springer Texts in Statistics
  • Produktform: Kartoniert, Previously published in hardcover
  • Gewicht: 955 g
  • Seiten: 619
  • Format (B x H x T): 155 x 235 x 35 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Measures and Integration: An Informal Introduction.- Measures.- Integration.- Lp-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.