Bayesian Procrustes analysis with applications to hydrology

Athanasios Micheas and Yuqiang Peng

Journal of Applied Statistics, 2010, vol. 37, issue 1, 41-55

Abstract: In this paper, we introduce Procrustes analysis in a Bayesian framework, by treating the classic Procrustes regression equation from a Bayesian perspective, while modeling shapes in two dimensions. The Bayesian approach allows us to compute point estimates and credible sets for the full Procrustes fit parameters. The methods are illustrated through an application to radar data from short-term weather forecasts (nowcasts), a very important problem in hydrology and meteorology.

Keywords: Bayesian computation and estimation; complex normal distribution; full Procrustes fit; Procrustes analysis; shape analysis (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1080/02664760802653560

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