Spatial analysis of wave direction data using wrapped Gaussian processes
From MaRDI portal
Publication:144889
DOI10.1214/12-AOAS576zbMATH Open1257.62094arXiv1301.1446OpenAlexW3104886058WikidataQ57014411 ScholiaQ57014411MaRDI QIDQ144889
Author name not available (Why is that?)
Publication date: 1 December 2012
Published in: (Search for Journal in Brave)
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.
Full work available at URL: https://arxiv.org/abs/1301.1446
No records found.
No records found.
This page was built for publication: Spatial analysis of wave direction data using wrapped Gaussian processes
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q144889)
