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Universal Consistency of Partitioning-Estimates of a Regression Function for Randomly Missing Data

  • A. Carbonez
  • L. Györfi
  • E. C. van der Meulen
Conference paper

Abstract

The weak and strong universal consistencies of partitioning estimates of a regression function are shown for incomplete sample. Here incomplete sample means that some sample points are missing according to a random missing mechanism operated on the observation vectors.

Keywords

Regression Function Nonparametric Regression Probability Weight Function Incomplete Sample Statistical Decision Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • A. Carbonez
    • 1
    • 2
  • L. Györfi
    • 1
    • 2
  • E. C. van der Meulen
    • 1
    • 2
  1. 1.Department of MathematicsKatholieke Universiteit LeuvenHeverleeBelgium
  2. 2.Hungarian Academy of SciencesTechnical University of BudapestBudapestHungary

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