A Comparison between Two Discordancy Tests to Identify Outlier in Wrapped Normal (WN) Samples

• Published in: Sains Malaysiana
• Main Author: Zulkefli N.M.; Rambli A.; Suhaimi M.I.K.A.; Mohamed I.; Redzuan R.S.
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171673986&doi=10.17576%2fjsm-2023-5207-19&partnerID=40&md5=790138f25e4b6075d3cde93218c26938

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. © 2023 Penerbit Universiti Kebangsaan Malaysia. All rights reserved.