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The identification of outliers in wrapped normal data by using ga statistics

This paper focuses on identifying outliers in the wrapped normal distribution. It is commonly found and when it is dealing with circular data, the existing of outliers will increase several problems.We will be using the existing statistics, the G a statistics to identify a single and patch of outlie...

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Main Authors: Sidik, Mohammad Illyas, Rambli, Adzhar, Mahmud, Zamalia, Redzuan, Raiha Shazween, Shahri, Nur Huda Nabihan Md
Format: Article
Published: Blue Eyes Intelligence Engineering & Sciences Publication 2019
Subjects:
HA Statistics
QA Mathematics
Online Access:http://eprints.um.edu.my/23435/
https://www.ijitee.org/wp-content/uploads/papers/v8i4s/DS2857028419.pdf
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spelling my.um.eprints.234352020-01-14T05:45:56Z http://eprints.um.edu.my/23435/ The identification of outliers in wrapped normal data by using ga statistics Sidik, Mohammad Illyas Rambli, Adzhar Mahmud, Zamalia Redzuan, Raiha Shazween Shahri, Nur Huda Nabihan Md HA Statistics QA Mathematics This paper focuses on identifying outliers in the wrapped normal distribution. It is commonly found and when it is dealing with circular data, the existing of outliers will increase several problems.We will be using the existing statistics, the G a statistics to identify a single and patch of outliers in the wrapped normal data. A Monte Carlo simulation will be carried out to generate the cut-off point’s value. The power performance of the discordancy test in circular data has been investigated. The increment of the contamination level, λ, large value of concentration parameter, ρ and large sample size, n will increase the performance of the outlier detection procedures. In addition, the result shows that the statistics performs well in detecting a patch of outliers in the data. As an illustration a practical example is presented by using the wind direction in Kota Bharu station. As conclusion, the G a statistics successfully detect outlier presence in this data set. © BEIESP. Blue Eyes Intelligence Engineering & Sciences Publication 2019 Article PeerReviewed Sidik, Mohammad Illyas and Rambli, Adzhar and Mahmud, Zamalia and Redzuan, Raiha Shazween and Shahri, Nur Huda Nabihan Md (2019) The identification of outliers in wrapped normal data by using ga statistics. International Journal of Innovative Technology and Exploring Engineering, 8 (4S). pp. 181-189. ISSN 2278-3075 https://www.ijitee.org/wp-content/uploads/papers/v8i4s/DS2857028419.pdf
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic HA Statistics
QA Mathematics
spellingShingle HA Statistics
QA Mathematics
Sidik, Mohammad Illyas
Rambli, Adzhar
Mahmud, Zamalia
Redzuan, Raiha Shazween
Shahri, Nur Huda Nabihan Md
The identification of outliers in wrapped normal data by using ga statistics
description This paper focuses on identifying outliers in the wrapped normal distribution. It is commonly found and when it is dealing with circular data, the existing of outliers will increase several problems.We will be using the existing statistics, the G a statistics to identify a single and patch of outliers in the wrapped normal data. A Monte Carlo simulation will be carried out to generate the cut-off point’s value. The power performance of the discordancy test in circular data has been investigated. The increment of the contamination level, λ, large value of concentration parameter, ρ and large sample size, n will increase the performance of the outlier detection procedures. In addition, the result shows that the statistics performs well in detecting a patch of outliers in the data. As an illustration a practical example is presented by using the wind direction in Kota Bharu station. As conclusion, the G a statistics successfully detect outlier presence in this data set. © BEIESP.
format Article
author Sidik, Mohammad Illyas
Rambli, Adzhar
Mahmud, Zamalia
Redzuan, Raiha Shazween
Shahri, Nur Huda Nabihan Md
author_facet Sidik, Mohammad Illyas
Rambli, Adzhar
Mahmud, Zamalia
Redzuan, Raiha Shazween
Shahri, Nur Huda Nabihan Md
author_sort Sidik, Mohammad Illyas
title The identification of outliers in wrapped normal data by using ga statistics
title_short The identification of outliers in wrapped normal data by using ga statistics
title_full The identification of outliers in wrapped normal data by using ga statistics
title_fullStr The identification of outliers in wrapped normal data by using ga statistics
title_full_unstemmed The identification of outliers in wrapped normal data by using ga statistics
title_sort identification of outliers in wrapped normal data by using ga statistics
publisher Blue Eyes Intelligence Engineering & Sciences Publication
publishDate 2019
url http://eprints.um.edu.my/23435/
https://www.ijitee.org/wp-content/uploads/papers/v8i4s/DS2857028419.pdf
_version_ 1657488209303568384
score 13.211869

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