Local superefficiency of data-driven projection density estimators in continuous time.

Bosq, Denis, and Blanke, Delphine. "Local superefficiency of data-driven projection density estimators in continuous time.." SORT 28.1 (2004): 37-54. <http://eudml.org/doc/40450>.

@article{Bosq2004,
abstract = {We construct a data-driven projection density estimator for continuous time processes. This estimator reaches superoptimal rates over a class F0 of densities that is dense in the family of all possible densities, and a «reasonable» rate elsewhere. The class F0 may be chosen previously by the analyst. Results apply to Rd-valued processes and to N-valued processes. In the particular case where square-integrable local time does exist, it is shown that our estimator is strictly better than the local time estimator over F0.},
author = {Bosq, Denis, Blanke, Delphine},
journal = {SORT},
keywords = {Inferencia no paramétrica; Procesos estocásticos; Estimadores; Función densidad de probabilidad; density estimation; data-driven; superefficiency; continuous time processes},
language = {eng},
number = {1},
pages = {37-54},
title = {Local superefficiency of data-driven projection density estimators in continuous time.},
url = {http://eudml.org/doc/40450},
volume = {28},
year = {2004},
}

TY - JOUR
AU - Bosq, Denis
AU - Blanke, Delphine
TI - Local superefficiency of data-driven projection density estimators in continuous time.
JO - SORT
PY - 2004
VL - 28
IS - 1
SP - 37
EP - 54
AB - We construct a data-driven projection density estimator for continuous time processes. This estimator reaches superoptimal rates over a class F0 of densities that is dense in the family of all possible densities, and a «reasonable» rate elsewhere. The class F0 may be chosen previously by the analyst. Results apply to Rd-valued processes and to N-valued processes. In the particular case where square-integrable local time does exist, it is shown that our estimator is strictly better than the local time estimator over F0.
LA - eng
KW - Inferencia no paramétrica; Procesos estocásticos; Estimadores; Función densidad de probabilidad; density estimation; data-driven; superefficiency; continuous time processes
UR - http://eudml.org/doc/40450
ER -