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Plug‐in bandwidth selector for recursive kernel regression estimators defined by stochastic approximation method
Author(s) -
Slaoui Yousri
Publication year - 2015
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/stan.12069
Subject(s) - estimator , bandwidth (computing) , stochastic approximation , regression function , mean squared error , kernel (algebra) , computer science , kernel regression , algorithm , regression , mathematics , mathematical optimization , statistics , discrete mathematics , computer network , computer security , key (lock)
In this paper, we propose an automatic selection of the bandwidth of the recursive kernel estimators of a regression function defined by the stochastic approximation algorithm. We showed that, using the selected bandwidth and the stepsize which minimize the mean weighted integrated squared error , the recursive estimator will be better than the non‐recursive one for small sample setting in terms of estimation error and computational costs. We corroborated these theoretical results through simulation study and a real dataset.