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Inference for circular distributions and processes.

Coles, Stuart (1998) Inference for circular distributions and processes. Statistics and Computing, 8 (2). pp. 105-113.

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Abstract

One approach to defining models for circular data and processes has been to take a standard Euclidean model and to wrap it around the circle. This generates rich families of circular models but creates difficulties for inference. Using data augmentation ideas which have previously been applied to this problem in the framework of an EM algorithm, we demonstrate the power and flexibility of Markov chain Monte Carlo methods to fit such classes of models to circular data. The precision of the technique is confirmed through simulated examples, and then applications are given to multivariate and time series data of wind directions.

Item Type: Article
Journal or Publication Title: Statistics and Computing
Uncontrolled Keywords: circle - directional data - Markov chain Monte Carlo - time series - wind directions - wrapped processes
Subjects: Q Science > QA Mathematics
Departments:
ID Code: 19450
Deposited By: ep_ss_importer
Deposited On: 18 Nov 2008 12:08
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:30
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/19450

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