A Bayesian model for longitudinal circular data
The analysis of short longitudinal series of circular data may be problematic and to some extent has not been completely developed. In this paper we present a Bayesian analysis of a model for such data. The model is based on a radial projection onto the circle of a particular bivariate normal distribution. Inferences about the parameters of the model are based on samples from the corresponding joint posterior density which are obtained using a Metropolis-within-Gibbs scheme after the introduction of suitable latent variables. The procedure is illustrated both using a simulated data set and a realdata set previously analyzed in the literature.
|Date of creation:||Sep 2011|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://portal.uc3m.es/portal/page/portal/dpto_estadistica
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gabriel Nunez-Antonio & Eduardo Gutierrez-Pena, 2005. "A Bayesian analysis of directional data using the projected normal distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(10), pages 995-1001.
- Rinaldo Artes, 2000. "Longitudinal Data Estimating Equations for Dispersion Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(2), pages 321-334.
When requesting a correction, please mention this item's handle: RePEc:cte:wsrepe:ws112720. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.