© Springer-Verlag 2007We investigate the asymptotic behavior of a robust version of local linear regression estimators with variable bandwidth for spatial associated processes. The weak consistency of the proposed estimators is given under appropriate conditions. Furthermore, we establish the asymptotic normality of the estimators, from which expressions for the asymptotic bias and variance can be derived.Chen Jia, Zhang Lixin and Li Degu
This paper considers the nonparametric M-estimator in a nonlinear cointegration type model. The loca...
International audienceWe investigate here a kernel estimate of A spatial regression function of a st...
In this dissertation, the analysis of spatial data through regression is investigated. Multiple obse...
We investigate the asymptotic behavior of a robust version of local linear regression estimators wit...
We study a robust version of local linear regression smoothers augmented with variable bandwidth. Th...
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. ...
When a linear model is used to analyze spatially correlated data, but the form of the spatial correl...
The estimation of the large-scale variability (spatial trend) of a geostatistical process can be acc...
Abstract We investigate the local linear M-estimation for regression in a fixed-design model when th...
We present a local linear estimator with variable bandwidth for multivariate non-parametric regressi...
In this paper, we study a nonlinear cointegration type model , where and are observed nonstationary ...
AbstractWe focus on nonparametric multivariate regression function estimation by locally weighted le...
We focus on nonparametric multivariate regression function estimation by locally weighted least squa...
In this paper, we consider M-estimators of the regression parameter in a spatial multiple linear reg...
In this paper, we establish the asymptotic normality through a Berry Esseen type bound, of a local l...
This paper considers the nonparametric M-estimator in a nonlinear cointegration type model. The loca...
International audienceWe investigate here a kernel estimate of A spatial regression function of a st...
In this dissertation, the analysis of spatial data through regression is investigated. Multiple obse...
We investigate the asymptotic behavior of a robust version of local linear regression estimators wit...
We study a robust version of local linear regression smoothers augmented with variable bandwidth. Th...
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. ...
When a linear model is used to analyze spatially correlated data, but the form of the spatial correl...
The estimation of the large-scale variability (spatial trend) of a geostatistical process can be acc...
Abstract We investigate the local linear M-estimation for regression in a fixed-design model when th...
We present a local linear estimator with variable bandwidth for multivariate non-parametric regressi...
In this paper, we study a nonlinear cointegration type model , where and are observed nonstationary ...
AbstractWe focus on nonparametric multivariate regression function estimation by locally weighted le...
We focus on nonparametric multivariate regression function estimation by locally weighted least squa...
In this paper, we consider M-estimators of the regression parameter in a spatial multiple linear reg...
In this paper, we establish the asymptotic normality through a Berry Esseen type bound, of a local l...
This paper considers the nonparametric M-estimator in a nonlinear cointegration type model. The loca...
International audienceWe investigate here a kernel estimate of A spatial regression function of a st...
In this dissertation, the analysis of spatial data through regression is investigated. Multiple obse...