Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)

Comparative Analysis Between L-Moments and Maximum Product Spacing Method for Extreme PM10 Concentration

Authors
Mohd Aftar Abu Bakar1, Noratiqah Mohd Ariff1, *, Mohd Shahrul Mohd Nadzir2
1Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Selangor, Malaysia
2Department of EarthSciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Selangor, Malaysia
*Corresponding author. Email: tqah@ukm.edu.my
Corresponding Author
Noratiqah Mohd Ariff
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-014-5_21How to use a DOI?
Keywords
L-Moments (LMOM); Maximum Product Spacing (MPS); Generalized Extreme Value (GEV); air quality
Abstract

There are several times where Malaysia suffers from severe air pollution, especially the urban and industrial area. The air quality stations across the country monitor various variables of air pollutants including particulate matter such as PM10. Due to harmful effects of pollution on human health and the environment, especially for extreme cases, air quality is a matter of worldwide concern amongst scientists, policy makers and public alike. In extreme value analysis, the generalized extreme value (GEV) distribution is widely adopted, and its parameters were estimated by various methods. Studies on these estimation methods are of great interest since reliable estimates are needed for modelling and forecasting extreme events. In this study, two methods based on order statistics are compared which are the L-moments (LMOM) and maximum product spacing (MPS) method. The L-moments method is a common method in extreme value analysis while MPS is considered as an alternative for maximum likelihood estimation (MLE) method. Both methods are applied on daily maximums of PM10 concentration at eight air quality monitoring stations in Peninsular Malaysia. Both methods provide a relatively close estimates and MPS is shown to be a reasonable alternative for parameter estimation of GEV distribution of extreme PM10 concentration in Malaysia.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

Volume Title
Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)
Series
Advances in Computer Science Research
Publication Date
12 December 2022
ISBN
10.2991/978-94-6463-014-5_21
ISSN
2352-538X
DOI
10.2991/978-94-6463-014-5_21How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Mohd Aftar Abu Bakar
AU  - Noratiqah Mohd Ariff
AU  - Mohd Shahrul Mohd Nadzir
PY  - 2022
DA  - 2022/12/12
TI  - Comparative Analysis Between L-Moments and Maximum Product Spacing Method for Extreme PM₁₀ Concentration
BT  - Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)
PB  - Atlantis Press
SP  - 214
EP  - 227
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-014-5_21
DO  - 10.2991/978-94-6463-014-5_21
ID  - Bakar2022
ER  -