Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6870435 | Computational Statistics & Data Analysis | 2014 | 14 Pages |
Abstract
The analysis of short longitudinal series of circular data may be problematic and to some extent has not been fully developed. A Bayesian analysis of a new model for such data is presented. The model is based on a radial projection onto the circle of a particular bivariate normal distribution. Inference about the parameters of the model is 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 using both simulated data sets and a real data set previously analyzed in the literature.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Gabriel Nuñez-Antonio, Eduardo Gutiérrez-Peña,