Size and shape analysis of landmark data

Abstract

SUMMARY The paper deals with statistical analysis of landmark data using the exact joint distribution theory for the size and shape of planar Gaussian configurations. This is an extension of earlier work which considered marginal shape analysis. Special cases of the size and shape distribution are examined and the isotropic Gaussian model is investigated in particular detail. Various properties are studied, including conditional distributions and a curve of regression. Finally we consider some possible approaches to inference, including exact maximum likelihood estimation of size and shape. A practical biological application is given which investigates the size and shape of mouse vertebrae.