This paper study about using of nonparametric models for Gross National Product data in Turkey and Stanford heart transplant data. It is discussed two nonparametric techniques called smoothing spline and kernel regression. The main goal is to compare the techniques used for prediction of the nonparametric regression models. According to the results of numerical studies, it is concluded that smoothing spline regression estimators are better than those of the kernel regression
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
So far, most of the researchers developed one type of estimator in nonparametric regression. But in ...
In daily life, mixed data patterns are often found, namely, those that change at a certain sub-inter...
The decline in the unemployment rate is an indication of the success of economic development in a co...
Nonparametric regression techniques are often sensitive to the presence of correlation in the errors...
We review different approaches to nonparametric density and regression estimation. Kernel estimators...
This paper studies nonparametric regression using smoothing splines. It proposes a method that combi...
Regression spline smoothing is a popular approach for conducting nonparametric regression
We consider nonparametric regression in a longitudinal marginal model of generalized estimating equa...
For independent data, it is well known that kernel methods and spline methods are essentially asympt...
Greiner A. Estimating penalized spline regressions: theory and application to economics. APPLIED ECO...
This article discusses on the smoothing parameter which is controlled by interpolating spline based ...
In this paper a new estimator for nonparametric regression is suggested. It is a smoothing-splines-l...
In this paper a new estimator for nonparametric regression is suggested. It is a smoothing-splines-l...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
So far, most of the researchers developed one type of estimator in nonparametric regression. But in ...
In daily life, mixed data patterns are often found, namely, those that change at a certain sub-inter...
The decline in the unemployment rate is an indication of the success of economic development in a co...
Nonparametric regression techniques are often sensitive to the presence of correlation in the errors...
We review different approaches to nonparametric density and regression estimation. Kernel estimators...
This paper studies nonparametric regression using smoothing splines. It proposes a method that combi...
Regression spline smoothing is a popular approach for conducting nonparametric regression
We consider nonparametric regression in a longitudinal marginal model of generalized estimating equa...
For independent data, it is well known that kernel methods and spline methods are essentially asympt...
Greiner A. Estimating penalized spline regressions: theory and application to economics. APPLIED ECO...
This article discusses on the smoothing parameter which is controlled by interpolating spline based ...
In this paper a new estimator for nonparametric regression is suggested. It is a smoothing-splines-l...
In this paper a new estimator for nonparametric regression is suggested. It is a smoothing-splines-l...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
We review different approaches to nonparametric density and regression estimation. Kernel estimators ...
So far, most of the researchers developed one type of estimator in nonparametric regression. But in ...
In daily life, mixed data patterns are often found, namely, those that change at a certain sub-inter...