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

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...

Full description

Bibliographic Details
Published in:MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES
Main Authors: Jamaliyatul, Nur Ain Al-Hameefatul; Mokhtar, Nurkhairany Amyra; Badyalina, Basri; Rambli, Adzhar; Zubairi, Yong Zulina
Format: Article
Language:English
Published: PENERBIT UTM PRESS 2024
Subjects:
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001221789500008
Description
Summary: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.
ISSN:2289-5981
2289-599X
DOI:10.11113/mjfas.v20n2.3342