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Detection of Outliers in Univariate Circular Data by Means of the Outlier Local Factor (LOF)

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  • Abuzaid Ali H.

    (Department of Mathematics, Al Azhar University, – Gaza, Palestine Israel .)

Abstract

The problem of outlier detection in univariate circular data was the object of increased interest over the last decade. New numerical and graphical methods were developed for samples from different circular probability distributions. The main drawback of the existing methods is, however, that they are distribution-based and ignore the problem of multiple outliers.

Suggested Citation

  • Abuzaid Ali H., 2020. "Detection of Outliers in Univariate Circular Data by Means of the Outlier Local Factor (LOF)," Statistics in Transition New Series, Polish Statistical Association, vol. 21(3), pages 39-51, September.
    • Handle: RePEc:vrs:stintr:v:21:y:2020:i:3:p:39-51:n:6
    DOI: 10.21307/stattrans-2020-043
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    References listed on IDEAS

    as
    1. D. Collett, 1980. "Outliers in Circular Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 50-57, March.
    2. Ali Abuzaid & Ibrahim Mohamed & Abdul Hussin, 2012. "Boxplot for circular variables," Computational Statistics, Springer, vol. 27(3), pages 381-392, September.
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