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
Recommended Citation
Kılıç, Muhammet Burak; Kalaylioglu, Zeynep; and Gupta, Ashis Sen, "A flexible Bayesian mixture approach for multi-modal circular data" (2022). Journal Articles. 3334.
https://digitalcommons.isical.ac.in/journal-articles/3334
Comments
Open Access, Bronze, Green