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In den WarenkorbZustand: New. In.
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In den WarenkorbPaperback. Zustand: Brand New. 164 pages. 9.00x6.00x0.50 inches. In Stock.
Sprache: Englisch
Verlag: Springer, Palgrave Macmillan, 2016
ISBN 10: 3319468219 ISBN 13: 9783319468211
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The canonical way to establish the central limit theorem for i.i.d. random variables is to use characteristic functions and Lévy's continuity theorem. This monograph focuses on this characteristic function approach and presents a renormalization theory called mod- convergence. This type of convergence is a relatively new concept with many deep ramifications, and has not previously been published in a single accessible volume. The authors construct an extremely flexible framework using this concept in order to study limit theorems and large deviations for a number of probabilistic models related to classical probability, combinatorics, non-commutative random variables, as well as geometric and number-theoretical objects.Intended for researchers in probability theory, the text is carefully well-written and well-structured, containing a great amount of detail and interesting examples.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Mod-¿ Convergence | Normality Zones and Precise Deviations | Valentin Féray (u. a.) | Taschenbuch | SpringerBriefs in Probability and Mathematical Statistics | xii | Englisch | 2016 | Springer | EAN 9783319468211 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | The canonical way to establish the central limit theorem for i.i.d. random variables is to use characteristic functions and Lévy¿s continuity theorem. This monograph focuses on this characteristic function approach and presents a renormalization theory called mod-¿ convergence. This type of convergence is a relatively new concept with many deep ramifications, and has not previously been published in a single accessible volume. The authors construct an extremely flexible framework using this concept in order to study limit theorems and large deviations for a number of probabilistic models related to classical probability, combinatorics, non-commutative random variables, as well as geometric and number-theoretical objects. Intended for researchers in probability theory, the text is carefully well-written and well-structured, containing a great amount of detail and interesting examples.