AbstractWe focus on nonparametric multivariate regression function estimation by locally weighted least squares. The asymptotic behavior for a sequence of error processes indexed by bandwidth matrices is derived. We discuss feasible data-driven consistent estimators minimizing asymptotic mean squared error or efficient estimators reducing asymptotic bias at points where opposite sign curvatures of the regression function are present in different directions
AbstractWe consider the kernel estimation of a multivariate regression function at a point. Theoreti...
We investigate the asymptotic behavior of a robust version of local linear regression estimators wit...
A decisive question in nonparametric smoothing techniques is the choice of the bandwidth or smoothin...
We focus on nonparametric multivariate regression function estimation by locally weighted least squa...
AbstractWe focus on nonparametric multivariate regression function estimation by locally weighted le...
AbstractConsider the nonparametric estimation of a multivariate regression function and its derivati...
We explore a class of vector smoothers based on local polynomial regression for fitting nonparametri...
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. ...
AbstractWe derive a functional limit theorem for a sequence of bandwidth processes with multivariate...
We present a local linear estimator with variable bandwidth for multivariate non-parametric regressi...
Automated bandwidth selection methods for nonparametric regression break down in the presence of cor...
We suggest an adaptive, error-dependent smoothing method for reducing the variance of local-linear c...
We study a robust version of local linear regression smoothers augmented with variable bandwidth. Th...
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
This paper studies robust estimation of multivariate regression model using kernel weighted local li...
AbstractWe consider the kernel estimation of a multivariate regression function at a point. Theoreti...
We investigate the asymptotic behavior of a robust version of local linear regression estimators wit...
A decisive question in nonparametric smoothing techniques is the choice of the bandwidth or smoothin...
We focus on nonparametric multivariate regression function estimation by locally weighted least squa...
AbstractWe focus on nonparametric multivariate regression function estimation by locally weighted le...
AbstractConsider the nonparametric estimation of a multivariate regression function and its derivati...
We explore a class of vector smoothers based on local polynomial regression for fitting nonparametri...
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. ...
AbstractWe derive a functional limit theorem for a sequence of bandwidth processes with multivariate...
We present a local linear estimator with variable bandwidth for multivariate non-parametric regressi...
Automated bandwidth selection methods for nonparametric regression break down in the presence of cor...
We suggest an adaptive, error-dependent smoothing method for reducing the variance of local-linear c...
We study a robust version of local linear regression smoothers augmented with variable bandwidth. Th...
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
This paper studies robust estimation of multivariate regression model using kernel weighted local li...
AbstractWe consider the kernel estimation of a multivariate regression function at a point. Theoreti...
We investigate the asymptotic behavior of a robust version of local linear regression estimators wit...
A decisive question in nonparametric smoothing techniques is the choice of the bandwidth or smoothin...