Title (Arabic)
Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data
DOI
10.33095/2cbwj529
Abstract
Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Error (MCE) criterion was used to compare the two models, leading to the conclusion that the Nadaraya-Watson (NW) circular model outperformed the parametric model in estimating the parameters of the circular regression model. Research, Practical & Social Implications: The recommendation emphasized using the Nadaraya-Watson nonparametric smoothing method to capture the nonlinearity in the data. Originality/value: The results indicated that the Nadaraya-Watson circular model (NW) outperformed the parametric model. Paper type Research paper.
Abstract (Arabic)
Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Error (MCE) criterion was used to compare the two models, leading to the conclusion that the Nadaraya-Watson (NW) circular model outperformed the parametric model in estimating the parameters of the circular regression model. Research, Practical & Social Implications: The recommendation emphasized using the Nadaraya-Watson nonparametric smoothing method to capture the nonlinearity in the data. Originality/value: The results indicated that the Nadaraya-Watson circular model (NW) outperformed the parametric model. Paper type Research paper.
Recommended Citation
Nazer, R. S., & Ali, O. A. (2024). Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data. Journal of Economics and Administrative Sciences, 30(144), 473-484. https://doi.org/10.33095/2cbwj529
First Page
473
Last Page
484
Rights
Copyright (c) 2024 Journal of Economics and Administrative Sciences
