A comparison between two discordancy tests to identify outlier in Wrapped Normal (WN) samples

Nurisha Mohd Zulkefli, and Adzhar Rambli, and Mohamad Ismeth Khan Azhar Suhaimi, and Ibrahim Mohamed, and Raiha Shazween Redzuan, (2023) A comparison between two discordancy tests to identify outlier in Wrapped Normal (WN) samples. Sains Malaysiana, 52 (7). pp. 2139-2148. ISSN 0126-6039

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Abstract

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.

Item Type:Article
Keywords:Circular data; Discordancy tests; Outliers; Wrapped normal distribution
Journal:Sains Malaysiana
ID Code:22599
Deposited By: Siti Zarenah Jasin
Deposited On:24 Nov 2023 03:21
Last Modified:27 Nov 2023 01:59

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