Coming Together of Bayesian Inference and Skew Spherical Data
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 usin...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Big Data |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2021.769726/full |
| _version_ | 1819274325264433152 |
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| author | Najmeh Nakhaei Rad Najmeh Nakhaei Rad Najmeh Nakhaei Rad Andriette Bekker Mohammad Arashi Mohammad Arashi Christophe Ley |
| author_facet | Najmeh Nakhaei Rad Najmeh Nakhaei Rad Najmeh Nakhaei Rad Andriette Bekker Mohammad Arashi Mohammad Arashi Christophe Ley |
| author_sort | Najmeh Nakhaei Rad |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-23T23:06:38Z |
| format | Article |
| id | doaj.art-c66942d5ceef43fe8ccca64f9edf9c33 |
| institution | Directory Open Access Journal |
| issn | 2624-909X |
| language | English |
| last_indexed | 2024-12-23T23:06:38Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Big Data |
| spelling | doaj.art-c66942d5ceef43fe8ccca64f9edf9c332022-12-21T17:26:48ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2022-02-01410.3389/fdata.2021.769726769726Coming Together of Bayesian Inference and Skew Spherical DataNajmeh Nakhaei Rad0Najmeh Nakhaei Rad1Najmeh Nakhaei Rad2Andriette Bekker3Mohammad Arashi4Mohammad Arashi5Christophe Ley6Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University, Mashhad, IranDSI-NRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-MaSS), Johannesburg, South AfricaDepartment of Statistics, University of Pretoria, Pretoria, South AfricaDepartment of Statistics, University of Pretoria, Pretoria, South AfricaDepartment of Statistics, University of Pretoria, Pretoria, South AfricaDepartment of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, BelgiumThis 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.https://www.frontiersin.org/articles/10.3389/fdata.2021.769726/fullFisher-von Mises-Langevin distributionGibbs samplingMCMC methodskew-rotationally-symmetric distributionsslice samplerspherical data |
| spellingShingle | Najmeh Nakhaei Rad Najmeh Nakhaei Rad Najmeh Nakhaei Rad Andriette Bekker Mohammad Arashi Mohammad Arashi Christophe Ley Coming Together of Bayesian Inference and Skew Spherical Data Frontiers in Big Data Fisher-von Mises-Langevin distribution Gibbs sampling MCMC method skew-rotationally-symmetric distributions slice sampler spherical data |
| title | Coming Together of Bayesian Inference and Skew Spherical Data |
| title_full | Coming Together of Bayesian Inference and Skew Spherical Data |
| title_fullStr | Coming Together of Bayesian Inference and Skew Spherical Data |
| title_full_unstemmed | Coming Together of Bayesian Inference and Skew Spherical Data |
| title_short | Coming Together of Bayesian Inference and Skew Spherical Data |
| title_sort | coming together of bayesian inference and skew spherical data |
| topic | Fisher-von Mises-Langevin distribution Gibbs sampling MCMC method skew-rotationally-symmetric distributions slice sampler spherical data |
| url | https://www.frontiersin.org/articles/10.3389/fdata.2021.769726/full |
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