A new multimodal and asymmetric bivariate circular distribution

Date

2018-09-01

Author

Hassanzadeh, Fatemeh
Kalaylioglu, Zeynep

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Multimodal and asymmetric bivariate circular data arise in several different disciplines and fitting appropriate distribution plays an important role in the analysis of such data. In this paper, we propose a new bivariate circular distribution which can be used to model both asymmetric and multimodal bivariate circular data simultaneously. In fact the proposed density covers unimodality as well as multimodality, symmetry as well as asymmetry of circular bivariate data. A number of properties of the proposed density are presented. A Bayesian approach with MCMC scheme is employed for statistical inference. Three real datasets and a simulation study are provided to illustrate the performance of the proposed model in comparison with alternative models such as finite mixture Cosine model.

Subject Keywords

Wind direction, Protein structure, Multimodal distribution, Circular bivariate data, Asymmetric distribution

URI

https://hdl.handle.net/11511/65585

Collections

Department of Statistics, Article