Proceedings of the 1st International Multidisciplinary Conference on Education, Technology, and Engineering (IMCETE 2019)

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Theoretical Study of Fourier Series Estimator in Semiparametric Regression for Longitudinal Data Based on Weighted Least Square Optimization

Authors
Kuzairi, N Chamidah, I N Budiantara
Corresponding Author
Kuzairi
Available Online 6 March 2020.
DOI
10.2991/assehr.k.200303.064How to use a DOI?
Keywords
Fourier, semiparametric regression, longitudinal data based
Abstract

Semiparametric regression approach is a combination of two components, namely the parametric regression component and the nonparametric regression component. The data used in this study is longitudinal data. Longitudinal data is data obtained from repeated observations of each subject at different time intervals. This data correlates to the same subject and is independent between different subjects. In this study the parametric component is assumed to be linear and the nonparametric component is approximated by the Fourier Series function. In this study, we determine the estimator for semiparametric regression parameters longitudinal data using Weighted Least Square (WLS). In the semiparametric regression based on Fourier series estimator for longitudinal data, the optimal oscillation parameter k will be selected. To get the estimation of model parameters, the WLS optimization is performed and GCV method is used to determine the optimal k. After obtaining the optimal oscillation parameters from the minimum GCV, the oscillation parameters are used again in the Fourier series semiparametric regression modeling. The criteria for goodness of the model use R2 and the value of MSE. The best model is a model that has a high R2 value and a small MSE value.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 1st International Multidisciplinary Conference on Education, Technology, and Engineering (IMCETE 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
6 March 2020
ISBN
978-94-6252-918-2
ISSN
2352-5398
DOI
10.2991/assehr.k.200303.064How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Kuzairi
AU  - N Chamidah
AU  - I N Budiantara
PY  - 2020
DA  - 2020/03/06
TI  - Theoretical Study of Fourier Series Estimator in Semiparametric Regression for Longitudinal Data Based on Weighted Least Square Optimization
BT  - Proceedings of the 1st International Multidisciplinary Conference on Education, Technology, and Engineering (IMCETE 2019)
PB  - Atlantis Press
SP  - 264
EP  - 267
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200303.064
DO  - 10.2991/assehr.k.200303.064
ID  - 2020
ER  -