Modern Nonparametric Statistics: Going Beyond Asymptotic Minimax

  • Lucien Birgé

    Université Paris VI, France
  • Iain M. Johnstone

    Stanford University, United States
  • Vladimir Spokoiny

    Weierstrass Institut für Angewandte Analysis und Stochastik, Berlin, Germany
Modern Nonparametric Statistics: Going Beyond Asymptotic Minimax cover
Download PDF

A subscription is required to access this article.

Abstract

During the years 1975-1990 a major emphasis in nonparametric estimation was put on computing the asymptotic minimax risk for many classes of functions. Modern statistical practice indicates some serious limitations of the asymptotic minimax approach and calls for some new ideas and methods which can cope with the numerous challenges brought to statisticians by modern sets of data.

Cite this article

Lucien Birgé, Iain M. Johnstone, Vladimir Spokoiny, Modern Nonparametric Statistics: Going Beyond Asymptotic Minimax. Oberwolfach Rep. 7 (2010), no. 1, pp. 883–939

DOI 10.4171/OWR/2010/16