Annals of Applied Statistics

Spatial analysis of wave direction data using wrapped Gaussian processes

Giovanna Jona-Lasinio, Alan Gelfand, and Mattia Jona-Lasinio

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Abstract

Directional data arise in various contexts such as oceanography (wave directions) and meteorology (wind directions), as well as with measurements on a periodic scale (weekdays, hours, etc.). Our contribution is to introduce a model-based approach to handle periodic data in the case of measurements taken at spatial locations, anticipating structured dependence between these measurements. We formulate a wrapped Gaussian spatial process model for this setting, induced from a customary linear Gaussian process.

We build a hierarchical model to handle this situation and show that the fitting of such a model is possible using standard Markov chain Monte Carlo methods. Our approach enables spatial interpolation (and can accommodate measurement error). We illustrate with a set of wave direction data from the Adriatic coast of Italy, generated through a complex computer model.

Article information

Source
Ann. Appl. Stat., Volume 6, Number 4 (2012), 1478-1498.

Dates
First available in Project Euclid: 27 December 2012

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1356629048

Digital Object Identifier
doi:10.1214/12-AOAS576

Mathematical Reviews number (MathSciNet)
MR3058672

Zentralblatt MATH identifier
1257.62094

Keywords
Bayesian kriging Gaussian processes hierarchical model latent variables

Citation

Jona-Lasinio, Giovanna; Gelfand, Alan; Jona-Lasinio, Mattia. Spatial analysis of wave direction data using wrapped Gaussian processes. Ann. Appl. Stat. 6 (2012), no. 4, 1478--1498. doi:10.1214/12-AOAS576. https://projecteuclid.org/euclid.aoas/1356629048


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