Add to ORKGThis paper provides a systematic and unified treatment of the developments in the area of kernel estimation in econometrics and statistics. Both the estimation and hypothesis testing issues are discussed for the nonparametric and semiparametric regression models. A discussion on the choice of windowwidth is also presented
Developments in the vast and growing literatures on nonparametric and semiparametric statistical est...
Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component...
Developments in the vast and growing literatures on nonparametric and semiparametric statistical est...
This paper provides a systematic and unified treatment of the developments in the area of kernel est...
This paper provides a systematic and unified treatment of the developments in the area of kernel est...
We review different approaches to nonparametric density and regression estimation. Kernel estimators...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
The paper gives an introduction to theory and application of multivariate and semipara metric kernel...
In a regression problem the relationship between an explanatory variable X and a response variable Y...
This paper study about using of nonparametric models for Gross National Product data in Turkey and S...
In this paper, we propose a combined regression estimator by using a parametric estimator and a nonp...
We explore the aims of, and relationships between, various kernel-type regression estimators. To do ...
We propose and study a class of regression models, in which the mean function is specified parametri...
We use ideas from estimating function theory to derive new simply computed consistent covariance ma...
Developments in the vast and growing literatures on nonparametric and semiparametric statistical est...
Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component...
Developments in the vast and growing literatures on nonparametric and semiparametric statistical est...
This paper provides a systematic and unified treatment of the developments in the area of kernel est...
This paper provides a systematic and unified treatment of the developments in the area of kernel est...
We review different approaches to nonparametric density and regression estimation. Kernel estimators...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
The paper gives an introduction to theory and application of multivariate and semipara metric kernel...
In a regression problem the relationship between an explanatory variable X and a response variable Y...
This paper study about using of nonparametric models for Gross National Product data in Turkey and S...
In this paper, we propose a combined regression estimator by using a parametric estimator and a nonp...
We explore the aims of, and relationships between, various kernel-type regression estimators. To do ...
We propose and study a class of regression models, in which the mean function is specified parametri...
We use ideas from estimating function theory to derive new simply computed consistent covariance ma...
Developments in the vast and growing literatures on nonparametric and semiparametric statistical est...
Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component...
Developments in the vast and growing literatures on nonparametric and semiparametric statistical est...