A flexible Bayesian mixture approach for multi-modal circular data

Article Type

Research Article

Publication Title

Hacettepe Journal of Mathematics and Statistics

Abstract

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 efficiency 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.

First Page

1160

Last Page

1173

DOI

10.15672/hujms.897144

Publication Date

1-1-2022

Comments

Open Access, Bronze, Green

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