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Article

Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator

1
Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Kotekli 48000, Turkey
2
Department of Mathematics and Statistics, Faculty of Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Jan Mielniczuk
Entropy 2021, 23(12), 1586; https://doi.org/10.3390/e23121586
Received: 19 October 2021 / Revised: 20 November 2021 / Accepted: 22 November 2021 / Published: 27 November 2021
This paper focuses on the adaptive spline (A-spline) fitting of the semiparametric regression model to time series data with right-censored observations. Typically, there are two main problems that need to be solved in such a case: dealing with censored data and obtaining a proper A-spline estimator for the components of the semiparametric model. The first problem is traditionally solved by the synthetic data approach based on the Kaplan–Meier estimator. In practice, although the synthetic data technique is one of the most widely used solutions for right-censored observations, the transformed data’s structure is distorted, especially for heavily censored datasets, due to the nature of the approach. In this paper, we introduced a modified semiparametric estimator based on the A-spline approach to overcome data irregularity with minimum information loss and to resolve the second problem described above. In addition, the semiparametric B-spline estimator was used as a benchmark method to gauge the success of the A-spline estimator. To this end, a detailed Monte Carlo simulation study and a real data sample were carried out to evaluate the performance of the proposed estimator and to make a practical comparison. View Full-Text
Keywords: adaptive splines; B-splines; right-censored data; semiparametric regression; synthetic data transformation; time series adaptive splines; B-splines; right-censored data; semiparametric regression; synthetic data transformation; time series
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MDPI and ACS Style

Aydın, D.; Ahmed, S.E.; Yılmaz, E. Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator. Entropy 2021, 23, 1586. https://doi.org/10.3390/e23121586

AMA Style

Aydın D, Ahmed SE, Yılmaz E. Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator. Entropy. 2021; 23(12):1586. https://doi.org/10.3390/e23121586

Chicago/Turabian Style

Aydın, Dursun, Syed Ejaz Ahmed, and Ersin Yılmaz. 2021. "Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator" Entropy 23, no. 12: 1586. https://doi.org/10.3390/e23121586

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