Empirical-Bias Bandwidths for Spatial Local Polynomial Regression with Correlated
Centre for Mathematical Sciences
Lund Institute of Technology,
The empirical-bias bandwidth selector (EBBS) is a method for data-driven
selection of bandwidths for local polynomial regression. It is a bandwidth
selection method for estimation of the mean-function and its partial derivatives
of any order as well as for estimation of the variance-function. Moreover
EBBS allows for univariate as well as multivariate
In this paper we introduce the empirical-bias bandwidth selector,
EBBSdep. This estimation procedure is adjusted to allow for dependent
errors and selection of diagonal or full bandwidth matrices for estimation
of the mean-function or one of its partial derivatives as well as for estimation
of the variance-function. Asymptotic results for the conditional bias of
the first order partial derivative
estimates are given for the local quadratic regression case.
A simulation study is performed to compare the adjusted and the original
version of EBBS with theoretical results for a few cases displaying varying
degrees of positive correlation.
Derivative estimation; heteroscedasticity; local bandwidth selection; surface
fitting; variance-function estimation.