A new test of discordancy in cylindrical data
Cylindrical data are bivariate data from the combination of circular and linear variables. However, up to now no work has been done on the detection of outlier in cylindrical data. We introduce a definition of outlier for cylindrical data and present a new test of discordancy to detect outlier in th...
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| Format: | Article |
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Taylor & Francis
2019
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| _version_ | 1825722089570566144 |
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| author | Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Shimizu, Kunio |
| author_facet | Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Shimizu, Kunio |
| author_sort | Sadikon, Nurul Hidayah |
| collection | UM |
| description | Cylindrical data are bivariate data from the combination of circular and linear variables. However, up to now no work has been done on the detection of outlier in cylindrical data. We introduce a definition of outlier for cylindrical data and present a new test of discordancy to detect outlier in this type of data, based on the k-nearest neighbor’s distance. Cut-off points of the new test statistic based on the Johnson-Wehrly distribution are calculated and its performance is examined using simulation. A practical example is presented using wind speed and wind direction data obtained from the Malaysian Meteorological Department. © 2018, © 2018 Taylor & Francis Group, LLC. |
| first_indexed | 2024-03-06T06:00:20Z |
| format | Article |
| id | um.eprints-23604 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T06:00:20Z |
| publishDate | 2019 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | um.eprints-236042020-01-28T02:47:37Z http://eprints.um.edu.my/23604/ A new test of discordancy in cylindrical data Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Shimizu, Kunio Q Science (General) QA Mathematics Cylindrical data are bivariate data from the combination of circular and linear variables. However, up to now no work has been done on the detection of outlier in cylindrical data. We introduce a definition of outlier for cylindrical data and present a new test of discordancy to detect outlier in this type of data, based on the k-nearest neighbor’s distance. Cut-off points of the new test statistic based on the Johnson-Wehrly distribution are calculated and its performance is examined using simulation. A practical example is presented using wind speed and wind direction data obtained from the Malaysian Meteorological Department. © 2018, © 2018 Taylor & Francis Group, LLC. Taylor & Francis 2019 Article PeerReviewed Sadikon, Nurul Hidayah and Ibrahim, Adriana Irawati Nur and Mohamed, Ibrahim and Shimizu, Kunio (2019) A new test of discordancy in cylindrical data. Communications in Statistics - Simulation and Computation, 48 (8). pp. 2512-2522. ISSN 0361-0918, DOI https://doi.org/10.1080/03610918.2018.1458131 <https://doi.org/10.1080/03610918.2018.1458131>. https://doi.org/10.1080/03610918.2018.1458131 doi:10.1080/03610918.2018.1458131 |
| spellingShingle | Q Science (General) QA Mathematics Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Shimizu, Kunio A new test of discordancy in cylindrical data |
| title | A new test of discordancy in cylindrical data |
| title_full | A new test of discordancy in cylindrical data |
| title_fullStr | A new test of discordancy in cylindrical data |
| title_full_unstemmed | A new test of discordancy in cylindrical data |
| title_short | A new test of discordancy in cylindrical data |
| title_sort | new test of discordancy in cylindrical data |
| topic | Q Science (General) QA Mathematics |
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