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.
Publié le : 1993-06-14
Classification:
Shape,
size-and-shape,
zonal polynomial,
Gaussian model,
configuration,
singular values,
distribution theory,
polar coordinates,
small variations,
QR decomposition,
62H10,
62H11,
62E15,
62E17
@article{1176349154,
author = {Goodall, Colin R. and Mardia, Kanti V.},
title = {Multivariate Aspects of Shape Theory},
journal = {Ann. Statist.},
volume = {21},
number = {1},
year = {1993},
pages = { 848-866},
language = {en},
url = {http://dml.mathdoc.fr/item/1176349154}
}
Goodall, Colin R.; Mardia, Kanti V. Multivariate Aspects of Shape Theory. Ann. Statist., Tome 21 (1993) no. 1, pp. 848-866. http://gdmltest.u-ga.fr/item/1176349154/