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A comparison between two discordancy tests to identify outlier in Wrapped Normal (WN) samples
Nurisha Mohd Zulkefli1, Adzhar Rambli2, Mohamad Ismeth Khan Azhar Suhaimi3, Ibrahim Mohamed4, Raiha Shazween Redzuan5.
This study focuses on comparing the performance of the Robust Circular Distance (RCDU*) (simplified version) and A statistics in detecting a single outlier in the Wrapped Normal (WN) samples. Firstly, this study proposes a simplified version of RCDU statistic. Then, the paper generates the cut-off points for both statistics taken from WN samples via a simulation study. This study also evaluates the performance of both statistics using the proportion of a correct outlier detection. As a result, for a small sample size, the performance of RCDU* and A statistics do not have a huge difference. However, for a large sample size of n=250, A statistic performs slightly better than RCDU* statistic. As an illustration of a practical example, both statistics successfully detected one outlier present in the wind direction data at Kota Bharu station.
Affiliation:
- Universiti Teknologi MARA, Malaysia
- Universiti Teknologi MARA, Malaysia
- Universiti Teknologi MARA, Malaysia
- University of Malaya, Malaysia
- University of Malaya, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Web of Science (SCIE - Science Citation Index Expanded) |
Impact Factor
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JCR (1.009) |
Rank |
Q4 (Multidisciplinary Sciences) |
Additional Information |
JCI (0.15) |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q2 (Multidisciplinary) |
Additional Information |
SJR (0.251) |
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