Covariance analysis for temporal data, with applications to DNA modelling

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Dryden, Ian L., Hill, Blake C., Wang, Hao and Laughton, Charles A. (2017) Covariance analysis for temporal data, with applications to DNA modelling. Stat . ISSN 2049-1573 (In Press)

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Abstract

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 which 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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/865323
Additional Information: This is the peer reviewed version of the following article: Dryden, I., Hill, B., Wang, H., and Laughton, C. (2017) Covariance analysis for temporal data, with applications to DNA modelling’, Stat, which has been published in final form at http://dx.doi.org/10.1002/sta4.149. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Keywords: Auto-regressive, covariance matrix, DNA, non-Euclidean, non-parametric, permutation test, size-and-shapes, temporal
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number: https://doi.org/10.1002/sta4.149
Depositing User: Dryden, Professor Ian
Date Deposited: 15 May 2017 08:04
Last Modified: 04 May 2020 18:49
URI: https://eprints.nottingham.ac.uk/id/eprint/42841

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