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Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events

A boxplot is an exploratory data analysis (EDA) tool for a compact visual display of a distributional summary of a univariate data set. It is designed to capture all typical observations and displays the location, spread, skewness and the tail of the data. The precision of some of this functionality...

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Main Authors: Babura, Babangida Ibrahim, Adam, Mohd Bakri, Fitrianto, Anwar, Abdul Samad @ Iammi, Abdul Rahim
Format: Article
Language:English
Published: Academy of Sciences Malaysia 2018
Online Access:http://psasir.upm.edu.my/id/eprint/72579/1/Enhancement%20of%20boxplot%20chrarcters%20.pdf
http://psasir.upm.edu.my/id/eprint/72579/
https://www.akademisains.gov.my/asmsj/article/enhancement-of-boxplot-characters-for-model-diagnostic-of-block-maximum-extremal-events/
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spelling my.upm.eprints.725792020-11-04T05:04:44Z http://psasir.upm.edu.my/id/eprint/72579/ Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events Babura, Babangida Ibrahim Adam, Mohd Bakri Fitrianto, Anwar Abdul Samad @ Iammi, Abdul Rahim A boxplot is an exploratory data analysis (EDA) tool for a compact visual display of a distributional summary of a univariate data set. It is designed to capture all typical observations and displays the location, spread, skewness and the tail of the data. The precision of some of this functionality is considered to be more reliable for symmetric data type and thus less appropriate for skewed data such as the extreme data. Many observations from extreme data were mistakenly marked as outliers by the Tukey’s standard boxplot. A new boxplot implementation is presented which adopts a fence definition using the extent of skewness and enhances the plot with additional features such as a quantile region for the parameters of generalized extreme value (GEV) distribution in fitting an extreme data set. The advantage of the new superimposed region was illustrated in term of batch comparison of extreme samples and an EDA tool to determine search region or direction as contained in the optimisation routines of a maximum likelihood parameter estimation of GEV model. A simulated and real-life data were used to justify the advantages of the boxplot enhancement. Academy of Sciences Malaysia 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/72579/1/Enhancement%20of%20boxplot%20chrarcters%20.pdf Babura, Babangida Ibrahim and Adam, Mohd Bakri and Fitrianto, Anwar and Abdul Samad @ Iammi, Abdul Rahim (2018) Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events. ASM Science Journal, 11 (2). 86 - 102. ISSN 1823-6782 https://www.akademisains.gov.my/asmsj/article/enhancement-of-boxplot-characters-for-model-diagnostic-of-block-maximum-extremal-events/
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description A boxplot is an exploratory data analysis (EDA) tool for a compact visual display of a distributional summary of a univariate data set. It is designed to capture all typical observations and displays the location, spread, skewness and the tail of the data. The precision of some of this functionality is considered to be more reliable for symmetric data type and thus less appropriate for skewed data such as the extreme data. Many observations from extreme data were mistakenly marked as outliers by the Tukey’s standard boxplot. A new boxplot implementation is presented which adopts a fence definition using the extent of skewness and enhances the plot with additional features such as a quantile region for the parameters of generalized extreme value (GEV) distribution in fitting an extreme data set. The advantage of the new superimposed region was illustrated in term of batch comparison of extreme samples and an EDA tool to determine search region or direction as contained in the optimisation routines of a maximum likelihood parameter estimation of GEV model. A simulated and real-life data were used to justify the advantages of the boxplot enhancement.
format Article
author Babura, Babangida Ibrahim
Adam, Mohd Bakri
Fitrianto, Anwar
Abdul Samad @ Iammi, Abdul Rahim
spellingShingle Babura, Babangida Ibrahim
Adam, Mohd Bakri
Fitrianto, Anwar
Abdul Samad @ Iammi, Abdul Rahim
Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
author_facet Babura, Babangida Ibrahim
Adam, Mohd Bakri
Fitrianto, Anwar
Abdul Samad @ Iammi, Abdul Rahim
author_sort Babura, Babangida Ibrahim
title Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
title_short Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
title_full Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
title_fullStr Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
title_full_unstemmed Enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
title_sort enhancement of boxplot chrarcters for model diagnostic of block maximum extremal events
publisher Academy of Sciences Malaysia
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/72579/1/Enhancement%20of%20boxplot%20chrarcters%20.pdf
http://psasir.upm.edu.my/id/eprint/72579/
https://www.akademisains.gov.my/asmsj/article/enhancement-of-boxplot-characters-for-model-diagnostic-of-block-maximum-extremal-events/
_version_ 1683232215284056064
score 13.211869

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