References
- Aitchison, J. (1983), “Principal Component Analysis of Compositional Data,” Biometrika, 70, 57–65. DOI: 10.1093/biomet/70.1.57.
- Box, G. E. P., and Cox, D. R. (1964), “An Analysis of Transformations” (with discussion), Journal of the Royal Statistical Society, Series B, 26, 211–252. DOI: 10.1111/j.2517-6161.1964.tb00553.x.
- Dryden, I. L., Koloydenko, A., and Zhou, D. (2009), “Non-Euclidean Statistics for Covariance Matrices, With Applications to Diffusion Tensor Imaging,” The Annals of Applied Statistics, 3, 1102–1123. DOI: 10.1214/09-AOAS249.
- Dryden, I. L., and Mardia, K. V. (2016), Statistical Shape Analysis, With Applications in R (2nd ed.), Chichester: Wiley.
- Dryden, I. L., Pennec, X., and Peyrat, J.-M. (2010), “Power Euclidean Metrics for Covariance Matrices With Application to Diffusion Tensor Imaging,” arXiv no. 1009.3045.
- Gablasova, D., Brezina, V., and McEnery, T. (2017), “Collocations in Corpus-Based Language Learning Research: Identifying, Comparing, and Interpreting the Evidence,” Language Learning, 67, 155–179. DOI: 10.1111/lang.12225.
- Ginestet, C. E., Li, J., Balachandran, P., Rosenberg, S., and Kolaczyk, E. D. (2017), “Hypothesis Testing for Network Data in Functional Neuroimaging,” The Annals of Applied Statistics, 11, 725–750. DOI: 10.1214/16-AOAS1015.
- Lele, S. (1993), “Euclidean Distance Matrix Analysis (EDMA): Estimation of Mean Form and Mean Form Difference,” Mathematical Geology, 25, 573–602. DOI: 10.1007/BF00890247.
- Marron, J. S., and Alonso, A. M. (2014), “Overview of Object Oriented Data Analysis,” Biometrical Journal, 56, 732–753. DOI: 10.1002/bimj.201300072.
- Masarotto, V., Panaretos, V. M., and Zemel, Y. (2018), “Procrustes Metrics on Covariance Operators and Optimal Transportation of Gaussian Processes,” Sankhya A. DOI: 10.1007/s13171-018-0130-1.
- Pigoli, D., Aston, J. A. D., Dryden, I. L., and Secchi, P. (2014), “Distances and Inference for Covariance Operators,” Biometrika, 101, 409–422. DOI: 10.1093/biomet/asu008.
- Scealy, J., and Welsh, A. (2014), “Colours and Cocktails: Compositional Data Analysis 2013 Lancaster Lecture,” Australian & New Zealand Journal of Statistics, 56, 145–169. DOI: 10.1111/anzs.12073.
- Severn, K. E., Dryden, I. L., and Preston, S. P. (2019), “Manifold Valued Data Analysis of Samples of Networks, With Applications in Corpus Linguistics,” arXiv no. 1902.08290.
- Tavakoli, S., Pigoli, D., Aston, J. A. D., and Coleman, J. S. (2019), “A Spatial Modeling Approach for Linguistic Object Data: Analysing Dialect Sound Variations Across Great Britain,” Journal of the American Statistical Association, this issue.
- Tsagris, M., Preston, S., and Wood, A. (2016), “Improved Classification for Compositional Data Using the α-Transformation,” Journal of Classification, 33, 243–261. DOI: 10.1007/s00357-016-9207-5.
- Wang, H., and Marron, J. S. (2007), “Object Oriented Data Analysis: Sets of Trees,” The Annals of Statistics, 35, 1849–1873. DOI: 10.1214/009053607000000217.