Fourier Series-Based Nonparametric Biresponse Regression for Climate Data Analysis

Hartina Husain (), Kusnaeni Kusnaeni, Wahyuni Eka Sasmita, Muhammad Rifki Nisardi and Nur Rahmi
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Hartina Husain: Bacharuddin Jusuf Habibie Institute of Technology
Kusnaeni Kusnaeni: Bacharuddin Jusuf Habibie Institute of Technology
Wahyuni Eka Sasmita: Bacharuddin Jusuf Habibie Institute of Technology
Muhammad Rifki Nisardi: Bacharuddin Jusuf Habibie Institute of Technology
Nur Rahmi: Bacharuddin Jusuf Habibie Institute of Technology

A chapter in Proceedings of the 9th International Conference on Accounting, Management, and Economics 2024 (ICAME 2024), 2025, pp 2346-2358 from Springer

Abstract: Abstract The biresponse Fourier series nonparametric regression is a model designed to analyze the relationship between two correlated response variables and multiple predictor variables, The model employs Fourier series to effectively capture periodic or cyclic patterns within the data, making itu particularly suited for climate-related applications. This study aims to estimate the parameters of a mixed semiparametric regression model applied to climate data, utilizing the Weighted Least Squares (WLS) method for estimation. The analysis was conducted on climate data from South Sulawesi and West Sulawesi, focusing on sunshine duration and wind speed as the two response variables. The results demonstrate that the optimal model includes one oscillation, achieving a minimum Generalized Cross Validation (GCV) value of 0.737 and a high Coefficient of Determination (R2) of 99.49%, indicating an excellent fit of the model to the data. These findings suggest that the biresponse Fourier series model is a powerful tool for climate data analysis, offering valuable insights into the cyclic nature of weather patterns in regions like South Sulawesi and West Sulawesi, where periodic variations in climate phenomena can be observed.

Keywords: Climate Change; Fourier Series; GCV; Regression (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-758-8_187

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