Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionApplied Mathematics and Computational Science Program
Spatio-Temporal Statistics and Data Analysis Group
Date
2014-03-05Online Publication Date
2014-03-05Print Publication Date
2014-09Permanent link to this record
http://hdl.handle.net/10754/563434
Metadata
Show full item recordAbstract
We propose notions of simplicial band depth for multivariate functional data that extend the univariate functional band depth. The proposed simplicial band depths provide simple and natural criteria to measure the centrality of a trajectory within a sample of curves. Based on these depths, a sample of multivariate curves can be ordered from the center outward and order statistics can be defined. Properties of the proposed depths, such as invariance and consistency, can be established. A simulation study shows the robustness of this new definition of depth and the advantages of using a multivariate depth versus the marginal depths for detecting outliers. Real data examples from growth curves and signature data are used to illustrate the performance and usefulness of the proposed depths. © 2014 Springer-Verlag Berlin Heidelberg.Citation
López-Pintado, S., Sun, Y., Lin, J. K., & Genton, M. G. (2014). Simplicial band depth for multivariate functional data. Advances in Data Analysis and Classification, 8(3), 321–338. doi:10.1007/s11634-014-0166-6Publisher
Springer Natureae974a485f413a2113503eed53cd6c53
10.1007/s11634-014-0166-6