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About this product
- DescriptionThe authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics - such as the classical central limit theorem - which are usually formulated in terms of convergence in distribution. Originated by Alfred Renyi, the tion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should t be missed by neglecting the tion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level with a solid kwledge of measure theoretic probability.
- Author BiographyErich Haeusler studied mathematics and physics at the University of Bochum from 1972 to 1978. He received his doctorate in mathematics in 1982 from the University of Munich. Since 1991 he has been Professor of Mathematics at the University of Giessen, where he teaches probability and mathematical statistics. Harald Luschgy studied mathematics, physics and mathematical logic at the Universities of Bonn and Munster. He received his doctorate in mathematics in 1976 from the University of Munster. He held visiting positions at the Universities of Hamburg, Bayreuth, Dortmund, Oldenburg, Passau and Wien and was a recipient of a Heisenberg grant from the DFG. Since 1995 he is Professor of Mathematics at the University of Trier where he teaches probability and mathematical statistics.
- Author(s)Erich Hausler,Harald Luschgy
- PublisherSpringer International Publishing AG
- Date of Publication09/06/2015
- Series TitleProbability Theory and Stochastic Modelling
- Series Part/Volume Number74
- Place of PublicationCham
- Country of PublicationSwitzerland
- ImprintSpringer International Publishing AG
- Content Notebiography
- Weight526 g
- Width155 mm
- Height235 mm
- Spine14 mm
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