All Outputs (2)

Size and shape analysis of error-prone shape data (2014)
Journal Article
Du, J., Dryden, I. L., & Huang, X. (2015). Size and shape analysis of error-prone shape data. Journal of the American Statistical Association, 110(509), https://doi.org/10.1080/01621459.2014.908779

We consider the problem of comparing sizes and shapes of objects when landmark data are prone to measurement error. We show that naive implementation of ordinary Procrustes analysis that ignores measurement error can compromise inference. To account... Read More about Size and shape analysis of error-prone shape data.

Distances and inference for covariance operators (2014)
Journal Article
Pigoli, D., Aston, J. A., Dryden, I. L., & Secchi, P. (2014). Distances and inference for covariance operators. Biometrika, 101(2), https://doi.org/10.1093/biomet/asu008

A framework is developed for inference concerning the covariance operator of a functional random process, where the covariance operator itself is an object of interest for statistical analysis. Distances for comparing positive-definite covariance mat... Read More about Distances and inference for covariance operators.