Depth classification based on affine-invariant, weighted and kernel-based spatial depth functions
Author
Source
Issue
Vol. 48, Issue 2 (30 Apr. 2021), pp.1-11, 11 p.
Publisher
Kuwait University Academic Publication Council
Publication Date
2021-04-30
Country of Publication
Kuwait
No. of Pages
11
Main Subjects
Arts & Humanities (Multidisciplinary)
Abstract EN
Several multivariate depth functions have been proposed in the literature, of which some satisfy all the conditions for statistical depth functions while some do not.
Spatial depth is known to be invariant to spherical and shift transformations.
In this paper, the possibility of using different versions of spatial depth in classification is considered.
The covariance-adjusted, weighted, and kernel-based versions of spatial depth functions are presented to classify multivariate outcomes.
We extend the maximal depth classification notions for the covariance-adjusted, weighted, and kernel-based spatial depth versions.
The classifiers' performance is considered and compared with some existing classification methods using simulated and real datasets.
American Psychological Association (APA)
Makinde, Olusola Samuel. 2021. Depth classification based on affine-invariant, weighted and kernel-based spatial depth functions. Kuwait Journal of Science،Vol. 48, no. 2, pp.1-11.
https://search.emarefa.net/detail/BIM-1500389
Modern Language Association (MLA)
Makinde, Olusola Samuel. Depth classification based on affine-invariant, weighted and kernel-based spatial depth functions. Kuwait Journal of Science Vol. 48, no. 2 (Apr. 2021), pp.1-11.
https://search.emarefa.net/detail/BIM-1500389
American Medical Association (AMA)
Makinde, Olusola Samuel. Depth classification based on affine-invariant, weighted and kernel-based spatial depth functions. Kuwait Journal of Science. 2021. Vol. 48, no. 2, pp.1-11.
https://search.emarefa.net/detail/BIM-1500389
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 10-11
Record ID
BIM-1500389