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Diagnostic analysis of a circular-circular regression model using asymmetric or asymmetric bi-modal circular errors

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  • Sungsu Kim
  • Md Monjurul Islam Rifat

Abstract

Many circular data sets encountered in practice are asymmetric or asymmetric bi-modal. In this paper, we propose a diagnostic analysis of a parametric circular regression model with a single circular explanatory variable by assuming asymmetric or asymmetric bi-modal circular errors. We develop a new test statistic for detecting outliers both in circular response and explanatory variables. For the case with a circular explanatory variable, we employ a parametric inverse circular-circular regression model. In addition, we provide a goodness of fit test to find whether circular errors are symmetric or not. Our methods are illustrated using a real data set arising from a study of Genomics.

Suggested Citation

  • Sungsu Kim & Md Monjurul Islam Rifat, 2021. "Diagnostic analysis of a circular-circular regression model using asymmetric or asymmetric bi-modal circular errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(12), pages 2848-2858, June.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:12:p:2848-2858
    DOI: 10.1080/03610926.2019.1676448
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    Cited by:

    1. Andrade, Ana C.C. & Pereira, Gustavo H.A. & Artes, Rinaldo, 2023. "The circular quantile residual," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).

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