Geodesic normal distribution on the circle
Jean-François Coeurjolly () and
Nicolas Bihan
Metrika: International Journal for Theoretical and Applied Statistics, 2012, vol. 75, issue 7, 977-995
Abstract:
This paper is concerned with the study of a circular random distribution called geodesic normal distribution recently proposed for general manifolds. This distribution, parameterized by two real numbers associated to some specific location and dispersion concepts, looks like a standard Gaussian on the real line except that the support of this variable is [0, 2π) and that the Euclidean distance is replaced by the geodesic distance on the circle. Some properties are studied and comparisons with the von Mises distribution in terms of intrinsic and extrinsic means and variances are provided. Finally, the problem of estimating the parameters through the maximum likelihood method is investigated and illustrated with some simulations. Copyright Springer-Verlag 2012
Keywords: Circular distribution; Geodesic distance; Intrinsic moments; Simulation; Maximum likelihood (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1007/s00184-011-0363-7 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:75:y:2012:i:7:p:977-995
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2
DOI: 10.1007/s00184-011-0363-7
Access Statistics for this article
Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze
More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().