Abstract
We place shape theory in the setting of noncentral multivariate analysis, and thus provide a comprehensive view of shape distributions when landmark coordinates are Gaussian distributed. This work allows the statistical analysis of shape to be carried out using standard techniques of multivariate analysis. The paper includes some new results in all dimensions and a general Gaussian approximation to the size-and-shape distribution. We also discuss some inference problems and give a numerical example.
Citation
Colin R. Goodall. Kanti V. Mardia. "Multivariate Aspects of Shape Theory." Ann. Statist. 21 (2) 848 - 866, June, 1993. https://doi.org/10.1214/aos/1176349154
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