Oberwolfach Reports

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Volume 7, Issue 1, 2010, pp. 883–939
DOI: 10.4171/OWR/2010/16

Published online: 2010-09-01

Modern Nonparametric Statistics: Going Beyond Asymptotic Minimax

Lucien Birgé[1], Iain M. Johnstone[2] and Vladimir Spokoiny[3]

(1) Université Paris VI, France
(2) Stanford University, United States
(3) Weierstrass Institut für Angewandte Analysis und Stochastik, Berlin, Germany

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.

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Birgé Lucien, Johnstone Iain, Spokoiny Vladimir: Modern Nonparametric Statistics: Going Beyond Asymptotic Minimax. Oberwolfach Rep. 7 (2010), 883-939. doi: 10.4171/OWR/2010/16