Uniformity in the Underlying Distribution

  • Aad W. van der Vaart
  • Jon A. Wellner
Part of the Springer Series in Statistics book series (SSS)


The previous chapters present empirical laws of large numbers and central limit theorems for observations from a fixed underlying distribution P. Many of the sufficient conditions given there are actually satisfied by very large classes of underlying measures; typically, the only limitation is finiteness of some appropriate moment of the envelope function. For instance, classes satisfying the uniform entropy condition are, up to measurability, Glivenko-Cantelli or Donsker for all P with P*F < ∞ or P*F 2 < ∞, respectively. In particular, many bounded classes of functions are universally Donsker: Donsker for every probability measure on the sample space.


Central Limit Theorem Empirical Process Envelope Function Brownian Bridge Uniform Version 
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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Aad W. van der Vaart
    • 1
  • Jon A. Wellner
    • 2
  1. 1.Department of Mathematics and Computer ScienceFree UniversityAmsterdamThe Netherlands
  2. 2.StatisticsUniversity of WashingtonSeattleUSA

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