We suggest a method for reducing variance in nonparametric surface estimation. The technique is applicable to a wide range of inferential problems, including both density estimation and regression, and to a wide variety of estimator types. It is based o
Abstract. We model a regression density nonparametrically so that at each value of the covariates th...
We introduce a data-perturbation method for reducing bias of a wide variety of density estimators, i...
In this article, we present and discuss three statistical methods for Surface Reconstruction. A typi...
AbstractWe suggest a method for reducing variance in nonparametric surface estimation. The technique...
[[abstract]]A variance reduction technique in nonparametric smoothing is proposed: at each point of ...
A new method for bias reduction in nonparametric density estimation is proposed. The method is a sim...
A new method for bias reduction in nonparametric density estimation is proposed. The method is a sim...
A transformation [phi] defined on a subset E of the real line and taking real values reduces the var...
We develop a variance reduction method for smoothing splines. For a given point of estimation, we de...
This paper is the second of a short series of articles aimed towards describing some of the various ...
Nonparametric inference for functional data over two-dimensional domains entails additional computat...
Abstract: A semiparametric estimate of a density may be formed via the convex combination of a param...
A technique is suggested for reducing the order of bias of kernel estimators by weighting the contri...
We model a regression density nonparametrically so that at each value of the covariates the density ...
We propose a nonparametric multiplicative bias corrected transformation estimator designed for heavy...
Abstract. We model a regression density nonparametrically so that at each value of the covariates th...
We introduce a data-perturbation method for reducing bias of a wide variety of density estimators, i...
In this article, we present and discuss three statistical methods for Surface Reconstruction. A typi...
AbstractWe suggest a method for reducing variance in nonparametric surface estimation. The technique...
[[abstract]]A variance reduction technique in nonparametric smoothing is proposed: at each point of ...
A new method for bias reduction in nonparametric density estimation is proposed. The method is a sim...
A new method for bias reduction in nonparametric density estimation is proposed. The method is a sim...
A transformation [phi] defined on a subset E of the real line and taking real values reduces the var...
We develop a variance reduction method for smoothing splines. For a given point of estimation, we de...
This paper is the second of a short series of articles aimed towards describing some of the various ...
Nonparametric inference for functional data over two-dimensional domains entails additional computat...
Abstract: A semiparametric estimate of a density may be formed via the convex combination of a param...
A technique is suggested for reducing the order of bias of kernel estimators by weighting the contri...
We model a regression density nonparametrically so that at each value of the covariates the density ...
We propose a nonparametric multiplicative bias corrected transformation estimator designed for heavy...
Abstract. We model a regression density nonparametrically so that at each value of the covariates th...
We introduce a data-perturbation method for reducing bias of a wide variety of density estimators, i...
In this article, we present and discuss three statistical methods for Surface Reconstruction. A typi...
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