OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Joint segmentation of wind speed and direction using a hierarchical model

Dobigeon, Nicolas and Tourneret, Jean-Yves Joint segmentation of wind speed and direction using a hierarchical model. (2007) Computational Statistics & Data Analysis, 5 (12). 5603-5621. ISSN 0167-9473

(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader

Official URL: http://dx.doi.org/10.1016/j.csda.2007.04.016


The problem of detecting changes in wind speed and direction is considered. Bayesian priors, with various degrees of certainty, are used to represent relationships between the two time series. Segmentation is then conducted using a hierarchical Bayesian model that accounts for correlations between the wind speed and direction. A Gibbs sampling strategy overcomes the computational complexity of the hierarchical model and is used to estimate the unknown parameters and hyperparameters. Extensions to other statistical models are also discussed. These models allow us to study other joint segmentation problems including segmentation of wave amplitude and direction. The performance of the proposed algorithms is illustrated with results obtained with synthetic and real data.

Item Type:Article
Additional Information:This publication is available on http://www.sciencedirect.com/science/journal/01679473
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Laboratory name:
Deposited On:08 Sep 2008 07:52

Repository Staff Only: item control page