2020 Nonparametric Regression Model for Longitudinal Data with Mixed Truncated Spline and Fourier Series
Made Ayu Dwi Octavanny, I. Nyoman Budiantara, Heri Kuswanto, Dyah Putri Rahmawati
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Abstr. Appl. Anal. 2020: 1-11 (2020). DOI: 10.1155/2020/4710745


Existing literature in nonparametric regression has established a model that only applies one estimator to all predictors. This study is aimed at developing a mixed truncated spline and Fourier series model in nonparametric regression for longitudinal data. The mixed estimator is obtained by solving the two-stage estimation, consisting of a penalized weighted least square (PWLS) and weighted least square (WLS) optimization. To demonstrate the performance of the proposed method, simulation and real data are provided. The results of the simulated data and case study show a consistent finding.


The authors are thankful for financial support via the PMDSU Grant (Batch III) from the Ministry of Education and Culture of the Republic of Indonesia.


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Made Ayu Dwi Octavanny. I. Nyoman Budiantara. Heri Kuswanto. Dyah Putri Rahmawati. "Nonparametric Regression Model for Longitudinal Data with Mixed Truncated Spline and Fourier Series." Abstr. Appl. Anal. 2020 1 - 11, 2020. https://doi.org/10.1155/2020/4710745


Received: 30 July 2020; Revised: 24 November 2020; Accepted: 1 December 2020; Published: 2020
First available in Project Euclid: 28 July 2020

Digital Object Identifier: 10.1155/2020/4710745

Rights: Copyright © 2020 Hindawi


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