TY - JOUR
T1 - Online estimation of a smooth regression function
AU - Khasminskii, R.
AU - Liptser, R.
PY - 2003
Y1 - 2003
N2 - The tracking (recursive) type estimator for a one-dimensional regression estimation problem with equidistant design is proposed. It is proven that, out of the inevitable initial layer, this estimator has the optimal rate of convergence of quadratic risk to zero if the sample size goes to infinity.
AB - The tracking (recursive) type estimator for a one-dimensional regression estimation problem with equidistant design is proposed. It is proven that, out of the inevitable initial layer, this estimator has the optimal rate of convergence of quadratic risk to zero if the sample size goes to infinity.
KW - Equidistant design
KW - Nonparametric estimation
KW - Online tracking estimator
KW - Regression
UR - http://www.scopus.com/inward/record.url?scp=0141429912&partnerID=8YFLogxK
U2 - 10.1137/S0040585X97979901
DO - 10.1137/S0040585X97979901
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AN - SCOPUS:0141429912
SN - 0040-585X
VL - 47
SP - 541
EP - 550
JO - Theory of Probability and its Applications
JF - Theory of Probability and its Applications
IS - 3
ER -