AUTHOR=Nakhaei Rad Najmeh , Bekker Andriette , Arashi Mohammad , Ley Christophe 

TITLE=Coming Together of Bayesian Inference and Skew Spherical Data

JOURNAL=Frontiers in Big Data

VOLUME=4

YEAR=2022

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2021.769726

DOI=10.3389/fdata.2021.769726

ISSN=2624-909X

ABSTRACT=<p>This paper presents Bayesian directional data modeling via the skew-rotationally-symmetric Fisher-von Mises-Langevin (FvML) distribution. The prior distributions for the parameters are a pivotal building block in Bayesian analysis, therefore, the impact of the proposed priors will be quantified using the Wasserstein Impact Measure (WIM) to guide the practitioner in the implementation process. For the computation of the posterior, modifications of Gibbs and slice samplings are applied for generating samples. We demonstrate the applicability of our contribution via synthetic and real data analyses. Our investigation paves the way for Bayesian analysis of skew circular and spherical data.</p>