Local linear-$k$NN smoothing for semi-functional partial linear regression

Kedir Nassima Houda; Benchikh Tawfik

Article Details

Local linear-$k$NN smoothing for semi-functional partial linear regression

Authors:

Kedir Nassima Houda | Benchikh Tawfik

Publisher:

Hacettepe University

Main Topics:

Statistics

Journal:

Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 2, pp.537-555

Document Type:

Article

Publication Date:

4/2024

Document Language:

English

Document ID (Org No.):

2001315600

pISSN:

2651-477X

Keywords:

Abstract:

 The aim of this paper is to study a semi-functional partial linear regression model. The estimators are constructed by k-nearest neighbors local linear method. Some asymptotic results are established for an i.i.d sample under certain conditions, including asymptotic normality of the parametric component and the almost certain convergence with rate of the non-parametric component. Lastly, using cross-validation, the performances of our estimation method are presented on simulated data and on real data by comparing them with other known approaches for semi-functional partial linear regression models.

 The aim of this paper is to study a semi-functional partial linear regression model. The estimators are constructed by k-nearest neighbors local linear method. Some asymptotic results are established for an i.i.d sample under certain conditions, including asymptotic normality of the parametric component and the almost certain convergence with rate of the non-parametric component. Lastly, using cross-validation, the performances of our estimation method are presented on simulated data and on real data by comparing them with other known approaches for semi-functional partial linear regression models.

 The aim of this paper is to study a semi-functional partial linear regression model. The estimators are constructed by k-nearest neighbors local linear method. Some asymptotic results are established for an i.i.d sample under certain conditions, including asymptotic normality of the parametric component and the almost certain convergence with rate of the non-parametric component. Lastly, using cross-validation, the performances of our estimation method are presented on simulated data and on real data by comparing them with other known approaches for semi-functional partial linear regression models.

 The aim of this paper is to study a semi-functional partial linear regression model. The estimators are constructed by k-nearest neighbors local linear method. Some asymptotic results are established for an i.i.d sample under certain conditions, including asymptotic normality of the parametric component and the almost certain convergence with rate of the non-parametric component. Lastly, using cross-validation, the performances of our estimation method are presented on simulated data and on real data by comparing them with other known approaches for semi-functional partial linear regression models.

Article Details

Local linear-$k$NN smoothing for semi-functional partial linear regression

Authors:

Kedir Nassima Houda | Benchikh Tawfik

Publisher:

Hacettepe University

Main Topics:

Statistics

Journal:

Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 2, pp.537-555

Document Type:

Article

Publication Date:

4/2024

Document Language:

English

Document ID (Org No.):

2001315600

pISSN:

2651-477X

Functional data analysis

partial linear regression

{\it k}NN estimation

local linear estimation

asymptotic normality

Issues

Article Details

Local linear-$k$NN smoothing for semi-functional partial linear regression

Authors: Kedir Nassima Houda | Benchikh Tawfik

Publisher: Hacettepe University

Main Topics: Statistics

Journal: Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 2, pp.537-555

Document Type: Article

Publication Date: 4/2024

Document Language: English

Document ID (Org No.): 2001315600

pISSN: 2651-477X

Functional data analysis

partial linear regression

{\it k}NN estimation

local linear estimation

asymptotic normality

Issues

Authors:

Kedir Nassima Houda | Benchikh Tawfik

Publisher:

Hacettepe University

Main Topics:

Statistics

Journal:

Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 2, pp.537-555

Document Type:

Article

Publication Date:

4/2024

Document Language:

English

Document ID (Org No.):

2001315600

pISSN:

2651-477X