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Empirical Distributions and Processes [electronic resource] : Selected Papers from a Meeting at Oberwolfach, March 28 – April 3, 1976 / edited by Peter Gaenssler, Pál Révész.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Mathematics ; 566Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1976Description: VII, 150 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540375159
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519.2 23
LOC classification:
  • QA273.A1-274.9
  • QA274-274.9
Online resources:
Contents:
Weak approximations of the empirical process when parameters are estimated -- On the Erdös-Rényi increments and the P. Lévy modulus of continuity of a kiefer process -- Kolmogorov-smirnov tests when parameters are estimated -- On uniform convergence of measures with applications to uniform convergence of empirical distributions -- An alternative approach to glivenko-cantelli theorems -- Weak convergence under contiguous alternatives of the empirical process when parameters are estimated: The Dk approach -- Almost sure invariance principles for empirical distribution functions of weakly dependent random variables -- Three theorems of multivariate empirical process -- Weak convergence to stable laws by means of a weak invariance principle -- A necessary condition for the convergence of the isotrope discrepancy -- Two examples concerning uniform convergence of measures w.r.t. balls in Banach spaces.
In: Springer eBooks
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Weak approximations of the empirical process when parameters are estimated -- On the Erdös-Rényi increments and the P. Lévy modulus of continuity of a kiefer process -- Kolmogorov-smirnov tests when parameters are estimated -- On uniform convergence of measures with applications to uniform convergence of empirical distributions -- An alternative approach to glivenko-cantelli theorems -- Weak convergence under contiguous alternatives of the empirical process when parameters are estimated: The Dk approach -- Almost sure invariance principles for empirical distribution functions of weakly dependent random variables -- Three theorems of multivariate empirical process -- Weak convergence to stable laws by means of a weak invariance principle -- A necessary condition for the convergence of the isotrope discrepancy -- Two examples concerning uniform convergence of measures w.r.t. balls in Banach spaces.

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