Covariance analysis for temporal data, with applications to DNA modelling

We introduce methodology for analysing the mean size-and-shape and covariance matrix of landmark data that are collected over time. Motivated by a study of DNA damage, we study some permutation-based tests for investigating significant differences in the structure of the mean and the variability/covariance of size and shape of point sets that evolve over time. The covariance matrix tests make use of some recently introduced metrics for comparing covariance matrices. We demonstrate that the tests have the correct significance level in various simulation studies, and we also investigate the relative power of the tests. Finally, we apply the procedures to the DNA datasets, providing practical insights into different types of DNA damage. Copyright (C) 2017 John Wiley & Sons, Ltd.