Segmentation of circular data

dc.contributor.author	Hawkins, Douglas M.
dc.contributor.author	Lombard, F.
dc.contributor.researchID	12950149 - Lombard, Frederick
dc.date.accessioned	2016-09-02T09:32:24Z
dc.date.available	2016-09-02T09:32:24Z
dc.date.issued	2015
dc.description.abstract	Circular data – data whose values lie in the interval [0,2π) – are important in a number of application areas. In some, there is a suspicion that a sequence of circular readings may contain two or more segments following different models. An analysis may then seek to decide whether there are multiple segments, and if so, to estimate the changepoints separating them. This paper presents an optimal method for segmenting sequences of data following the von Mises distribution. It is shown by example that the method is also successful in data following a distribution with much heavier tails	en_US
dc.identifier.citation	Hawkins, D.M. & Lombard, F. 2015. Segmentation of circular data. Journal of applied statistics, 42(1):88-97. [http://dx.doi.org/10.1080/02664763.2014.934665]	en_US
dc.identifier.issn	0266-4763
dc.identifier.issn	1360-0532 (Online)
dc.identifier.uri	http://hdl.handle.net/10394/18518
dc.identifier.uri	http://dx.doi.org/10.1080/02664763.2014.934665
dc.identifier.uri	http://www.tandfonline.com/doi/full/10.1080/02664763.2014.934665
dc.language.iso	en	en_US
dc.publisher	Taylor & Francis	en_US
dc.subject	Von Mises distribution	en_US
dc.subject	changepoints	en_US
dc.subject	model selection	en_US
dc.title	Segmentation of circular data	en_US
dc.type	Article	en_US

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