Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship

Authors

  • Nur Ain Al-Hameefatul Jamaliyatul Mathematical Sciences Studies, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA (UiTM), Johor Branch, Segamat Campus, Segamat, Johor, Malaysia
  • Nurkhairany Amyra Mokhtar Mathematical Sciences Studies, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA (UiTM), Johor Branch, Segamat Campus, Segamat, Johor, Malaysia
  • Basri Badyalina Mathematical Sciences Studies, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA (UiTM), Johor Branch, Segamat Campus, Segamat, Johor, Malaysia
  • Adzhar Rambli School of Mathematical Sciences, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
  • Yong Zulina Zubairi Institute of Advanced Studies, Universiti Malaya, Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.11113/mjfas.v20n2.3342

Keywords:

Simultaneous Linear Functional Relationship Model, Fisher Information Matrix, Maximum Likelihood Estimation, Linear Variables

Abstract

The extension of parameter estimation from a bivariate linear functional relationship model (LFRM) to simultaneous LFRM for linear variables using the maximum likelihood estimation (MLE) method is explored in this paper. The covariance matrix of the parameter estimates is derived through the Fisher information matrix. A simulation study was done to investigate the performance of the parameter estimation. According to the simulation study, the estimated parameters have a small bias. The beauty of simultaneous LFRM lies in developing the model to study the relationship between more than two linear variables while considering error terms for all variables. The applicability of the proposed simultaneous model is demonstrated using wind speed, humidity, and temperature data from Butterworth and Melaka during the southwest monsoon season of 2020.

References

Arif, A. M., Zubairi, Y. G., & Hussin, A. G. (2019). On Robust estimation for slope in linear functional relationship model. Sains Malaysiana, 48(1), 237-242. https://doi.org/10.17576/jsm-2019-4801-27.

Arif, A. M., Zubairi, Y. Z., & Hussin, A. G. (2020a). Parameter estimation in replicated linear functional relationship model in the presence of outliers. Malaysian Journal of Fundamental and Applied Sciences, 16(2), 158-160. https://doi.org/10.11113/mjfas.v16n2.1633.

Arif, A. M., Zubairi, Y. Z., & Hussin, A. G. (2020b). Parameter estimation in replicated linear functional relationship model in the presence of outliers. Malaysian Journal of Fundamental and Applied Sciences, 16(2), 158-160. https://doi.org/10.11113/mjfas.v16n2.1633.

Arif, A. M., Zubairi, Y. Z., & Hussin, A. G. (2021). COVRATIO Statistic for replicated linear functional relationship model. Journal of Physics: Conference Series, 1988(1). https://doi.org/10.1088/1742-6596/1988/1/012100.

Arif, A. M., Zubairi, Y. Z., & Hussin, A. G. (2022). Outlier detection in balanced replicated linear functional relationship model. Sains Malaysiana, 51(2), 599-607. https://doi.org/10.17576/jsm-2022-5102-23.

Arif, A. M., Zubairi, Yong Zulina, & Hussin, Abdul Ghapor. (2021a). Maximum likelihood estimation of replicated linear functional relationship model. Applied Mathematics and Computational Intelligence, 10(1), 301-308.

Fah, C. Y., Rijal, O. M., & Abu Bakar, S. A. R. (2010). Multidimensional unreplicated linear functional relationship model with single slope and its coefficient of determination. WSEAS Transactions on Mathematics, 9(5), 295-313.

Ghapor, A. A., Zubairi, Y. Z., Mamun, A. S. M. A., & Imon, A. H. M. R. (2014). On detecting outlier in simple linear functional relationship model using covratio statistic. Pakistan Journal of Statistics, 30(1), 129-142.

Ghapor, A. A., Zubairi, Y. Z., Mamun, A. S. M. A., & Imon, A. H. M. R. (2015). A robust nonparametric slope estimation in linear functional relationship model. Pakistan Journal of Statistics, 48(1), 339-350. https://doi.org/10.17576/jsm-2019-4801-27.

Gillard, J. (2010). An overview of linear structural models in errors in variables regression. Revstat Statistical Journal, 8(1), 57-80.

Hawkins, D. I., & Kanji, G. K. (1995). 100 Statistical Tests. Journal of Marketing Research, 32(1), 112. https://doi.org/10.2307/3152117.

Hussin, A., Salleh, E., Chan, H. Y., & Mat, S. (2015). The reliability of predicted mean vote model predictions in an air-conditioned mosque during daily prayer times in Malaysia. Architectural Science Review, 58(1), 67-76. https://doi.org/10.1080/00038628.2014.976538.

Jamaliyatul, N. A. A. H., Badyalina, B., Mokhtar, N. A., Rambli, A., Zubairi, Y. Z., & Abdul Ghapor, A. (2023). Modelling wind speed data in Pulau Langkawi with functional relationship. Sains Malaysiana, 52(8), 2419-2430.

Kendall, M. G., & Stuart, A. (1973). The Advanced Theory of Statistics. London: Griffin.

Laporan Tahunan 2020 (p. 73). (2020). Jabatan Meteorologi Malaysia.

Lindley, D. V. (1947). Regression Lines and the linear functional relationship. Journal of the Royal Statistical Society, 9(2), 218-244.

Lo Brano, V., Orioli, A., Ciulla, G., & Culotta, S. (2011). Quality of Wind speed fitting distributions for the urban area of Palermo, Italy. Renewable Energy, 36(3), 1026-1039. https://doi.org/10.1016/j.renene.2010.09.009.

Manteghi, G., Mostofa, T., & Md. Noor, M. P. B. (2020). A field investigation on the impact of the wider water body on-air, surface temperature and physiological equivalent temperature at Malacca Town. International Journal of Environmental Science and Development, 11(6), 286-289. https://doi.org/10.18178/ijesd.2020.11.6.1264.

Massey, F. J. (1951). The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, 46(253), 68. https://doi.org/10.2307/2280095.

Mokhtar, N. A., Badyalina, B., & Zubairi, Y. Z. (2022b). Functional model of wind direction data in Kuching, Sarawak, Malaysia. Applied Mathematical Sciences,16(7), 349-357.

Mokhtar, N. A., Zubairi, Y. Z., & Hussin, A. G. (2015). Parameter estimation of simultaneous linear functional relationship model for circular variables assuming equal error variances. Pakistan Journal of Statistics, 31(2).

Mokhtar, N. A., Zubairi, Y. Z., Hussin, A. G., Badyalina, B., Ghazali, A. F., Ya’Acob, F. F., Shamala, P., & Kerk, L. C. (2021a). Modelling wind direction data of Langkawi Island during Southwest monsoon in 2019 to 2020 using bivariate linear functional relationship model with von Mises distribution. Journal of Physics: Conference Series, 1988(1). https://doi.org/10.1088/1742-6596/1988/1/012097.

Nelder, J. (1977). Theory and application of linear-model-Graybill, FA. Journal of the Royal Statistical Society, Series A (Statistics in Society), 140, 384-385.

Zakaria, M. N. (2022). The limitation of widely used data normality tests in clinical research. Auditory and Vestibular Research, 31(1), 1-3. https://doi.org/10.18502/avr.v31i1.8127.

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Published

24-04-2024