Reference : Coming Together of Bayesian Inference and Skew Spherical Data
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Mathematics
Human health sciences : Orthopedics, rehabilitation & sports medicine
http://hdl.handle.net/10993/51298
Coming Together of Bayesian Inference and Skew Spherical Data
English
Ley, Christophe mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH) >]
Nakhaei Rad, Najmeh [University of Pretoria > Department of Statistics]
Bekker, Andriette [University of Pretoria > Department of Statistics]
Arashi, Mohammad [Ferdowsi University of Mashhad > Faculty of Mathematical Sciences - Department of Statistic]
8-Feb-2022
Frontiers in Big Data
Frontiers Media S.A.
Yes
2624-909X
CH
[en] 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.
http://hdl.handle.net/10993/51298
https://www.frontiersin.org/articles/10.3389/fdata.2021.769726/full

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