P.J. Paine
An elliptically symmetric angular Gaussian distribution
Paine, P.J.; Preston, Simon P.; Tsagris, Michail; Wood, Andrew T.A.
Authors
SIMON PRESTON simon.preston@nottingham.ac.uk
Professor of Statistics and Applied Mathematics
Michail Tsagris
Andrew T.A. Wood
Abstract
We define a distribution on the unit sphere Sd−1 called the elliptically symmetric angular Gaussian distribution. This distribution, which to our knowledge has not been studied before, is a subfamily of the angular Gaussian distribution closely analogous to the Kent subfamily of the general Fisher–Bingham distribution. Like the Kent distribution, it has ellipse-like contours, enabling modelling of rotational asymmetry about the mean direction, but it has the additional advantages of being simple and fast to simulate from, and having a density and hence likelihood that is easy and very quick to compute exactly. These advantages are especially beneficial for computationally intensive statistical methods, one example of which is a parametric bootstrap procedure for inference for the directional mean that we describe.
Citation
Paine, P., Preston, S. P., Tsagris, M., & Wood, A. T. (2018). An elliptically symmetric angular Gaussian distribution. Statistics and Computing, 28(3), 689-697. https://doi.org/10.1007/s11222-017-9756-4
Journal Article Type | Article |
---|---|
Acceptance Date | May 9, 2017 |
Online Publication Date | May 22, 2017 |
Publication Date | 2018-05 |
Deposit Date | May 23, 2017 |
Publicly Available Date | May 23, 2017 |
Journal | Statistics and Computing |
Print ISSN | 0960-3174 |
Electronic ISSN | 1573-1375 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 28 |
Issue | 3 |
Pages | 689-697 |
DOI | https://doi.org/10.1007/s11222-017-9756-4 |
Keywords | Angular Gaussian, Bootstrap, Kent distribution, Spherical distribution |
Public URL | https://nottingham-repository.worktribe.com/output/861491 |
Publisher URL | http://link.springer.com/article/10.1007%2Fs11222-017-9756-4 |
Contract Date | May 23, 2017 |
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
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