Adaptive non-asymptotic confidence balls in density estimation
ESAIM: Probability and Statistics, Tome 16 (2012), pp. 61-85
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We build confidence balls for the common density s of a real valued sample X1,...,Xn. We use resampling methods to estimate the projection of s onto finite dimensional linear spaces and a model selection procedure to choose an optimal approximation space. The covering property is ensured for all n ≥ 2 and the balls are adaptive over a collection of linear spaces.
DOI :
10.1051/ps/2010012
Classification :
62G07, 62G09, 62G10, 62G15
Keywords: confidence balls, density estimation, resampling methods
Keywords: confidence balls, density estimation, resampling methods
@article{PS_2012__16__61_0,
author = {Lerasle, Matthieu},
title = {Adaptive non-asymptotic confidence balls in density estimation},
journal = {ESAIM: Probability and Statistics},
pages = {61--85},
year = {2012},
publisher = {EDP-Sciences},
volume = {16},
doi = {10.1051/ps/2010012},
mrnumber = {2946120},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.1051/ps/2010012/}
}
TY - JOUR AU - Lerasle, Matthieu TI - Adaptive non-asymptotic confidence balls in density estimation JO - ESAIM: Probability and Statistics PY - 2012 SP - 61 EP - 85 VL - 16 PB - EDP-Sciences UR - http://geodesic.mathdoc.fr/articles/10.1051/ps/2010012/ DO - 10.1051/ps/2010012 LA - en ID - PS_2012__16__61_0 ER -
Lerasle, Matthieu. Adaptive non-asymptotic confidence balls in density estimation. ESAIM: Probability and Statistics, Tome 16 (2012), pp. 61-85. doi: 10.1051/ps/2010012
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