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JP Journal of Biostatistics

JP Journal of Biostatistics
Volume 23, Issue 2, Pages 211 - 225 (July 2023)
http://dx.doi.org/10.17654/0973514323012

APPLICATION OF ROBUST REGRESSION ON SEA SURFACE TEMPERATURE DATA IN THE INDIAN OCEAN

Norizan Mohamed, Nur Ain Natasha Baharin, Nur Sabrina Mohamad Ikram, Nor Azlida Aleng, Maharani A. Bakar, Siti Madhihah Abdul Malik, Nur Fadhilah Ibrahim and Miftahuddin

Abstract:

Sea Surface Temperature (SST) is the temperature of the water near an ocean’s surface. It plays a critical role in the interaction of the Earth’s surface and atmosphere. However, not all time series data on SST are complete to affect climate change prediction. To address such issues, the median imputation is used to deal with the missing data. In data analysis, outlier is unavoidable, and robust statistical methods are required. The presence of outlier which is common in the dataset leads to an error in the result. To remedy this problem, the robust regression has been proposed. The missing values of SST in the Indian Ocean got imputed by using the median imputation approach. We then construct the robust regression model using the S-estimator and LTS-estimator. The R-squared (R²) values of the S-estimator and LTS-estimator were 0.5670 and 0.6033, respectively. When the data was contaminated with 1%, 2%, 3%, 4% and 5% outliers, the R² values of the LTS-estimator were 0.5899, 0.5811, 0.5740, 0.5767 and 0.5699. The study’s findings revealed that the LTS-estimator is a better model compared to the S-estimator in terms of robustness, as is evidenced by the highest R²-value.

Keywords and phrases:

Sea Surface Temperature (SST), median imputation, S-estimator, LTS-estimator, R-squared R².

Received: February 6, 2023; Accepted: March 15, 2023; Published: June 7, 2023

How to cite this article: Norizan Mohamed, Nur Ain Natasha Baharin, Nur Sabrina Mohamad Ikram, Nor Azlida Aleng, Maharani A. Bakar, Siti Madhihah Abdul Malik, Nur Fadhilah Ibrahim and Miftahuddin, Application of robust regression on sea surface temperature data in the Indian Ocean, JP Journal of Biostatistics 23(2) (2023), 211-225. http://dx.doi.org/10.17654/0973514323012

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

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