In this paper, we propose a method to select the better of two types of models: a polynomial with low degree and a S-spline model, using the commoninformation criterion. The methodology can be directly applied to semi-parametric multiple regression analysis
Abstract: Nonparametric response transformations for regression models are of great interest and use...
The ordinary least squares (OLS) method had been extensively applied to estimation of d...
Graduation date: 2014We consider two semiparametric regression models for data analysis, the stochas...
In this paper, we propose a method to select the better of two types of models: a polynomial with lo...
Abstract: A flexible nonparametric regression model is considered in which the response de-pends lin...
Three types of polynomial mixed model splines have been proposed: smoothing splines, P-splines and p...
Three types of polynomial mixed model splines have been proposed: smoothing splines, P-splines and p...
While polynomial regression models on a one-dimensional interval have received broad attention in op...
In a range of practical applications where a response cannot be adequately described by a low order ...
A new methodology for creating highly accurate, static nonlinear maps from scattered, multivariate d...
Spline functions provide a useful and flexible basis for modeling relationships with continuous pred...
Copyright © 2013 Desale Habtzghi, Jin-Hong Park. This is an open access article distributed under th...
Polynomial spline regression models of low degree have proved useful in modeling responses from desi...
We discuss design aspects of d-th degree polynomial spline regression with prescribed knots over a c...
In this paper, the relationship between X, the structure matrix in a polynomial regression (PR) mode...
Abstract: Nonparametric response transformations for regression models are of great interest and use...
The ordinary least squares (OLS) method had been extensively applied to estimation of d...
Graduation date: 2014We consider two semiparametric regression models for data analysis, the stochas...
In this paper, we propose a method to select the better of two types of models: a polynomial with lo...
Abstract: A flexible nonparametric regression model is considered in which the response de-pends lin...
Three types of polynomial mixed model splines have been proposed: smoothing splines, P-splines and p...
Three types of polynomial mixed model splines have been proposed: smoothing splines, P-splines and p...
While polynomial regression models on a one-dimensional interval have received broad attention in op...
In a range of practical applications where a response cannot be adequately described by a low order ...
A new methodology for creating highly accurate, static nonlinear maps from scattered, multivariate d...
Spline functions provide a useful and flexible basis for modeling relationships with continuous pred...
Copyright © 2013 Desale Habtzghi, Jin-Hong Park. This is an open access article distributed under th...
Polynomial spline regression models of low degree have proved useful in modeling responses from desi...
We discuss design aspects of d-th degree polynomial spline regression with prescribed knots over a c...
In this paper, the relationship between X, the structure matrix in a polynomial regression (PR) mode...
Abstract: Nonparametric response transformations for regression models are of great interest and use...
The ordinary least squares (OLS) method had been extensively applied to estimation of d...
Graduation date: 2014We consider two semiparametric regression models for data analysis, the stochas...
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