NONPARAMETRIC REGRESSION ANALYSIS BASED ON RATIONAL (Padé) APPROXIMATION FOR CENSORED-DATA
| Autor: | Dursun Aydin, Ersin Yilmaz |
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| Rok vydání: | 2020 |
| Předmět: |
Basic Sciences
Temel Bilimler Data transformation (statistics) General Medicine Synthetic data Nonparametric regression Data point Transformation (function) Pade approximation right-censored data kernel smoothing truncated total least squares Kernel smoother Applied mathematics Total least squares Smoothing Mathematics |
| Zdroj: | Volume: 21, Issue: 7-16 Eskişehir Technical University Journal of Science and Technology A-Applied Sciences and Engineering |
| ISSN: | 2667-4211 |
| Popis: | This paper considers the estimation of a nonparametric regression model with randomly right-censored data. To estimate the model, rational (Padé) approximation based on truncated total least squares (P-TTLS) is used as a smoothing method. Because of censored, data points cannot be used directly in modeling process, a data transformation is needed for overcoming this problem. As known, synthetic data transformation assigns censored points as zero and gives additional magnitudes to uncensored ones associated with Kaplan-Meier distribution of the censored dataset. Thus, the differences between censored and uncensored observations grow which causes a kind of spatial variation in the shape of data. In this paper, to bring a solution to this problematic situation, P-TTLS is used that works well on spatial variation. Also, to see the performance of the P-TTLS on censored data modeling, a simulation study is carried out and it is compared with the benchmarked kernel smoothing (B-KS) method to observe how P-TTLS behaves. |
| Databáze: | OpenAIRE |
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