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...

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Published in:Malaysian Journal of Fundamental and Applied Sciences
Main Author: Jamaliyatul N.A.A.-H.; Mokhtar N.A.; Badyalina B.; Rambli A.; Zubairi Y.Z.
Format: Article
Language:English
Published: Penerbit UTM Press 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192242941&doi=10.11113%2fmjfas.v20n2.3342&partnerID=40&md5=1265296aad79f57d00b7d0e0e712b7b1
id 2-s2.0-85192242941
spelling 2-s2.0-85192242941
Jamaliyatul N.A.A.-H.; Mokhtar N.A.; Badyalina B.; Rambli A.; Zubairi Y.Z.
Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
2024
Malaysian Journal of Fundamental and Applied Sciences
20
2
10.11113/mjfas.v20n2.3342
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192242941&doi=10.11113%2fmjfas.v20n2.3342&partnerID=40&md5=1265296aad79f57d00b7d0e0e712b7b1
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. ©Copyright Jamaliyatul.
Penerbit UTM Press
2289599X
English
Article
All Open Access; Gold Open Access
author Jamaliyatul N.A.A.-H.; Mokhtar N.A.; Badyalina B.; Rambli A.; Zubairi Y.Z.
spellingShingle Jamaliyatul N.A.A.-H.; Mokhtar N.A.; Badyalina B.; Rambli A.; Zubairi Y.Z.
Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
author_facet Jamaliyatul N.A.A.-H.; Mokhtar N.A.; Badyalina B.; Rambli A.; Zubairi Y.Z.
author_sort Jamaliyatul N.A.A.-H.; Mokhtar N.A.; Badyalina B.; Rambli A.; Zubairi Y.Z.
title Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
title_short Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
title_full Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
title_fullStr Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
title_full_unstemmed Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
title_sort Modelling Wind Speed, Humidity, and Temperature in Butterworth and Melaka during Southwest Monsoon in 2020 with a Simultaneous Linear Functional Relationship
publishDate 2024
container_title Malaysian Journal of Fundamental and Applied Sciences
container_volume 20
container_issue 2
doi_str_mv 10.11113/mjfas.v20n2.3342
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192242941&doi=10.11113%2fmjfas.v20n2.3342&partnerID=40&md5=1265296aad79f57d00b7d0e0e712b7b1
description 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. ©Copyright Jamaliyatul.
publisher Penerbit UTM Press
issn 2289599X
language English
format Article
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
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