Given a sample from some unknown continuous density f : ℝ→ℝ, we construct adaptive confidence bands that are honest for all densities in a “generic” subset of the union of t-Hölder balls, 0
Publié le : 2010-04-15
Classification:
Adaptive estimation,
limit theorem,
density estimation,
extremes,
Gaussian processes,
wavelet estimators,
kernel estimators,
62G07,
60F05
@article{1266586625,
author = {Gin\'e, Evarist and Nickl, Richard},
title = {Confidence bands in density estimation},
journal = {Ann. Statist.},
volume = {38},
number = {1},
year = {2010},
pages = { 1122-1170},
language = {en},
url = {http://dml.mathdoc.fr/item/1266586625}
}
Giné, Evarist; Nickl, Richard. Confidence bands in density estimation. Ann. Statist., Tome 38 (2010) no. 1, pp. 1122-1170. http://gdmltest.u-ga.fr/item/1266586625/