Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar

In practical applications of statistical modelling, the phenomena under investigation often involve many data points representing rare events with extremely high or low values compared to the typical range. These extreme events can significantly impact the data distribution, exhibiting long and heav...

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Main Author: Jaafar, Zuraida
Format: Monograph
Language:English
Published: Universiti Teknologi MARA, Negeri Sembilan 2024
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Online Access:https://ir.uitm.edu.my/id/eprint/105591/1/105591.pdf
https://ir.uitm.edu.my/id/eprint/105591/
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spelling my.uitm.ir.1055912024-11-05T04:13:48Z https://ir.uitm.edu.my/id/eprint/105591/ Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar Jaafar, Zuraida L Education (General) In practical applications of statistical modelling, the phenomena under investigation often involve many data points representing rare events with extremely high or low values compared to the typical range. These extreme events can significantly impact the data distribution, exhibiting long and heavy tails. The occurrence of extreme events can be observed across various disciplines, including climatology, earth sciences, ecology, engineering, hydrology, and social sciences. However, a critical question arises in extreme events analysis: How far can we reliably determine the extremity of data? One of the most fundamental problems in the field of extreme value models is selecting a threshold value, a boundary or cutoff point used to determine the extremity of the data (McPhillips et al., 2018). The choice of the thresholds needs to be done properly, as a high threshold value will reduce the bias but increase the variance for the estimators while choosing a low value will give the opposite effect (Scarrott & MacDonald, 2012). Choosing the appropriate threshold value can help ensure that these extreme values are accurately identified and included in the analysis, leading to more accurate predictions and better decision-making. Universiti Teknologi MARA, Negeri Sembilan 2024-10 Monograph NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/105591/1/105591.pdf Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar. (2024) Bulletin. Universiti Teknologi MARA, Negeri Sembilan.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic L Education (General)
spellingShingle L Education (General)
Jaafar, Zuraida
Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar
description In practical applications of statistical modelling, the phenomena under investigation often involve many data points representing rare events with extremely high or low values compared to the typical range. These extreme events can significantly impact the data distribution, exhibiting long and heavy tails. The occurrence of extreme events can be observed across various disciplines, including climatology, earth sciences, ecology, engineering, hydrology, and social sciences. However, a critical question arises in extreme events analysis: How far can we reliably determine the extremity of data? One of the most fundamental problems in the field of extreme value models is selecting a threshold value, a boundary or cutoff point used to determine the extremity of the data (McPhillips et al., 2018). The choice of the thresholds needs to be done properly, as a high threshold value will reduce the bias but increase the variance for the estimators while choosing a low value will give the opposite effect (Scarrott & MacDonald, 2012). Choosing the appropriate threshold value can help ensure that these extreme values are accurately identified and included in the analysis, leading to more accurate predictions and better decision-making.
format Monograph
author Jaafar, Zuraida
author_facet Jaafar, Zuraida
author_sort Jaafar, Zuraida
title Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar
title_short Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar
title_full Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar
title_fullStr Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar
title_full_unstemmed Extreme event analysis: estimating boundaries for data extremity / Zuraida Jaafar
title_sort extreme event analysis: estimating boundaries for data extremity / zuraida jaafar
publisher Universiti Teknologi MARA, Negeri Sembilan
publishDate 2024
url https://ir.uitm.edu.my/id/eprint/105591/1/105591.pdf
https://ir.uitm.edu.my/id/eprint/105591/
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