fdacluster-package: fdacluster: Joint Clustering and Alignment of Functional Data

In fdacluster: Joint Clustering and Alignment of Functional Data

fdacluster: Joint Clustering and Alignment of Functional Data

Description

Implementations of the k-means, hierarchical agglomerative and DBSCAN clustering methods for functional data which allows for jointly aligning and clustering curves. It supports functional data defined on one-dimensional domains but possibly evaluating in multivariate codomains. It supports functional data defined in arrays but also via the 'fd' and 'funData' classes for functional data defined in the 'fda' and 'funData' packages respectively. It currently supports shift, dilation and affine warping functions for functional data defined on the real line and uses the SRSF framework to handle boundary-preserving warping for functional data defined on a specific interval. Main reference for the k-means algorithm: Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean alignment for curve clustering" \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.csda.2009.12.008")}. Main reference for the SRSF framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013) "Generative models for functional data using phase and amplitude separation" \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.csda.2012.12.001")}.

Author(s)

Maintainer: Aymeric Stamm [e-mail] (ORCID)

Other contributors:

• Laura Sangalli [e-mail] [contributor]

• Piercesare Secchi [e-mail] [contributor]

• Simone Vantini [e-mail] [contributor]

• Valeria Vitelli [e-mail] [contributor]

• Alessandro Zito [e-mail] [contributor]

References

Arthur, D., and S. Vassilvitskii. 2007. “K-Means++ the Advantages of Careful Seeding.” In Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 1027–35.

Marron, J. S., J. O. Ramsay, L. M. Sangalli, and A. Srivastava. 2014. “Statistics of Time Warpings and Phase Variations.”

Marron, J. S., J. O. Ramsay, L. M. Sangalli, and A. Srivastava. 2015. “Functional Data Analysis of Amplitude and Phase Variation.” Statistical Science, 468–84.

Ramsay, J., and B. W. Silverman. 2005. Functional Data Analysis. Springer Series in Statistics. Springer.

Sangalli, L. M., P. Secchi, S. Vantini, and V. Vitelli. 2010. “K-Mean Alignment for Curve Clustering.” Computational Statistics & Data Analysis 54 (5): 1219–33.

Tucker, J. D., W. Wu, and A. Srivastava. 2013. “Generative Models for Functional Data Using Phase and Amplitude Separation.” Computational Statistics & Data Analysis 61: 50–66.

Vantini, S. 2012. “On the Definition of Phase and Amplitude Variability in Functional Data Analysis.” Test 21 (4): 676–96. https://doi.org/10.1007/s11749-011-0268-9.

See Also

Useful links:

• https://astamm.github.io/fdacluster/index.html

• https://github.com/astamm/fdacluster

fdacluster documentation built on July 9, 2023, 6:45 p.m.