AbstractRates of convergence for nonparametric regression estimators based on recursive partitioning schemes are derived. The central idea is to consider the tree-structured regression estimator as a wavelet estimator based on the orthogonal system of Haar functions. A locally adaptive data-driven smoothing method is proposed and its performance is studied
We show that a nonparametric estimator of a regression function, obtained as solution of a specific ...
In this paper we focus on nonparametric estimation of a constrained regression function using penali...
Vita.Two research areas that have generated a great deal of interest in the field of statistics are ...
AbstractRates of convergence for nonparametric regression estimators based on recursive partitioning...
This paper considers an unknown functional estimation problem in a regression model with multiplicat...
Semiparametric regression models have a linear part as in the linear regression and a nonlinear part...
Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of spatially-...
Wavelet thresholding methods, especially those which pool information from geometric structures in t...
In this thesis, we investigate some adaptive wavelet approaches for a so-called nonparametric regres...
We show that for nonparametric regression if the samples have random uniform design, the wavelet met...
International audienceWe consider the estimation of an unknown regression function from a nonparamet...
Wavelet-based regression analysis is widely used mostly for equally-spaced designs. For such designs...
In this paper one approach is proposed for using wavelets in non parametric regression estimation. T...
In the setting of nonparametric stochastic regression, we introduce a new way to build smooth design...
We present a new approach of nonparametric regression with wavelets if the design is stochastic. In ...
We show that a nonparametric estimator of a regression function, obtained as solution of a specific ...
In this paper we focus on nonparametric estimation of a constrained regression function using penali...
Vita.Two research areas that have generated a great deal of interest in the field of statistics are ...
AbstractRates of convergence for nonparametric regression estimators based on recursive partitioning...
This paper considers an unknown functional estimation problem in a regression model with multiplicat...
Semiparametric regression models have a linear part as in the linear regression and a nonlinear part...
Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of spatially-...
Wavelet thresholding methods, especially those which pool information from geometric structures in t...
In this thesis, we investigate some adaptive wavelet approaches for a so-called nonparametric regres...
We show that for nonparametric regression if the samples have random uniform design, the wavelet met...
International audienceWe consider the estimation of an unknown regression function from a nonparamet...
Wavelet-based regression analysis is widely used mostly for equally-spaced designs. For such designs...
In this paper one approach is proposed for using wavelets in non parametric regression estimation. T...
In the setting of nonparametric stochastic regression, we introduce a new way to build smooth design...
We present a new approach of nonparametric regression with wavelets if the design is stochastic. In ...
We show that a nonparametric estimator of a regression function, obtained as solution of a specific ...
In this paper we focus on nonparametric estimation of a constrained regression function using penali...
Vita.Two research areas that have generated a great deal of interest in the field of statistics are ...