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Covariance analysis for temporal data, with applications to DNA modelling

Dryden, Ian L.; Hill, Blake C.; Wang, Hao; Laughton, Charles A.

Authors

Ian L. Dryden ian.dryden@nottingham.ac.uk

Blake C. Hill

Hao Wang

Charles A. Laughton



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.

Journal Article Type Article
Publication Date Jun 13, 2017
Journal Stat
Electronic ISSN 2049-1573
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 6
Issue 1
Pages 218-230
APA6 Citation Dryden, I. L., Hill, B. C., Wang, H., & Laughton, C. A. (2017). Covariance analysis for temporal data, with applications to DNA modelling. Stat, 6(1), 218-230. doi:10.1002/sta4.149
DOI https://doi.org/10.1002/sta4.149
Keywords Auto-regressive, covariance matrix, DNA, non-Euclidean, non-parametric, permutation test, size-and-shapes, temporal
Publisher URL http://onlinelibrary.wiley.com/doi/10.1002/sta4.149/full
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
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.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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