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
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
The local polynomial estimator is particularly affected by the curse of di- mensionality. So, the p...
We explore a class of vector smoothers based on local polynomial regression for fitting nonparametri...
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...
AbstractThis paper studies improvements of multivariate local linear regression. Two intuitively app...
AbstractWe consider the kernel estimation of a multivariate regression function at a point. Theoreti...
In this article, we introduce and study local constant and local linear nonparametric regression est...
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. ...
We suggest an adaptive, error-dependent smoothing method for reducing the variance of local-linear c...
AbstractWe derive a functional limit theorem for a sequence of bandwidth processes with multivariate...
Automated bandwidth selection methods for nonparametric regression break down in the presence of cor...
We study a robust version of local linear regression smoothers augmented with variable bandwidth. Th...
Local linear methods are applied to a nonparametric regression model with normal errors in the varia...
We present a local linear estimator with variable bandwidth for multivariate non-parametric regressi...
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
The local polynomial estimator is particularly affected by the curse of di- mensionality. So, the p...
We explore a class of vector smoothers based on local polynomial regression for fitting nonparametri...
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...
AbstractThis paper studies improvements of multivariate local linear regression. Two intuitively app...
AbstractWe consider the kernel estimation of a multivariate regression function at a point. Theoreti...
In this article, we introduce and study local constant and local linear nonparametric regression est...
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. ...
We suggest an adaptive, error-dependent smoothing method for reducing the variance of local-linear c...
AbstractWe derive a functional limit theorem for a sequence of bandwidth processes with multivariate...
Automated bandwidth selection methods for nonparametric regression break down in the presence of cor...
We study a robust version of local linear regression smoothers augmented with variable bandwidth. Th...
Local linear methods are applied to a nonparametric regression model with normal errors in the varia...
We present a local linear estimator with variable bandwidth for multivariate non-parametric regressi...
Abstract: Local linear kernel methods have been shown to dominate local constant methods for the non...
The local polynomial estimator is particularly affected by the curse of di- mensionality. So, the p...
We explore a class of vector smoothers based on local polynomial regression for fitting nonparametri...