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Mod-? Convergence: Normality Zones and Precise Deviations

AUTHOR Mliot, Pierre-Loc; Fray, Valentin; Nikeghbali, Ashkan et al.
PUBLISHER Springer (12/16/2016)
PRODUCT TYPE Paperback (Paperback)

Description
The canonical way to establish the central limit theorem for i.i.d. random variables is to use characteristic functions and Lvy's continuity theorem. This monograph focuses on this characteristic function approach and presents a renormalization theory called mod-ϕ 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.
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Product Details
ISBN-13: 9783319468211
ISBN-10: 3319468219
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
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Page Count: 152
Carton Quantity: 46
Product Dimensions: 6.14 x 0.35 x 9.21 inches
Weight: 0.53 pound(s)
Feature Codes: Bibliography, Illustrated
Country of Origin: NL
Subject Information
BISAC Categories
Mathematics | Probability & Statistics - General
Mathematics | Number Theory
Mathematics | Combinatorics
Dewey Decimal: 511.6
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The canonical way to establish the central limit theorem for i.i.d. random variables is to use characteristic functions and Lvy's continuity theorem. This monograph focuses on this characteristic function approach and presents a renormalization theory called mod-ϕ 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.
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Your Price  $54.44
Paperback