Published January 1, 2022
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A flexible Bayesian mixture approach for multi-modal circular data
- 1. Burdur Mehmet Akif Ersoy Univ, Dept Business Adm, Quantitat Methods Unit, Burdur, Turkey
- 2. Middle East Tech Univ, Dept Stat, Ankara, Turkey
Description
In this article, we consider multi-modal circular data and nonparametric inference. We introduce a doubly flexible method based on Dirichlet process circular mixtures in which parameter assumptions are relaxed. We assess and discuss in simulation studies the effi-ciency of the proposed extension relative to the standard finite mixture applications in the analysis of multi-modal circular data. The real data application shows that this relaxed approach is promising for making important contributions to our understanding of many real-life phenomena particularly in environmental sciences such as animal orientations.
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