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Covariance analysis for temporal data, with applications to DNA modelling
Author(s) -
Dryden Ian,
Hill Blake,
Wang Hao,
Laughton Charles
Publication year - 2017
Publication title -
stat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 18
ISSN - 2049-1573
DOI - 10.1002/sta4.149
Subject(s) - covariance , covariance matrix , permutation (music) , computer science , analysis of covariance , covariance intersection , statistics , estimation of covariance matrices , covariance function , resampling , data mining , algorithm , mathematics , physics , acoustics
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 © 2017 John Wiley & Sons, Ltd.