Back to Search
Start Over
Depth-Based Recognition of Shape Outlying Functions
- Source :
- Journal of Computational and Graphical Statistics. 26:883-893
- Publication Year :
- 2017
- Publisher :
- Informa UK Limited, 2017.
-
Abstract
- © 2017 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. A major drawback of many established depth functionals is their ineffectiveness in identifying functions outlying merely in shape. Herein, a simple modification of functional depth is proposed to provide a remedy for this difficulty. The modification is versatile, widely applicable, and introduced without imposing any assumptions on the data, such as differentiability. It is shown that many favorable attributes of the original depths for functions, including consistency properties, remain preserved for the modified depths. The powerfulness of the new approach is demonstrated on a number of examples for which the known depths fail to identify the outlying functions. Supplementary material for this article is available online. ispartof: Journal of Computational and Graphical Statistics vol:26 issue:4 pages:883-893 status: published
- Subjects :
- Statistics and Probability
05 social sciences
01 natural sciences
010104 statistics & probability
Simple (abstract algebra)
Consistency (statistics)
0502 economics and business
Econometrics
Discrete Mathematics and Combinatorics
0101 mathematics
Statistics, Probability and Uncertainty
Algorithm
050205 econometrics
Mathematics
Drawback
Subjects
Details
- ISSN :
- 15372715 and 10618600
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Journal of Computational and Graphical Statistics
- Accession number :
- edsair.doi.dedup.....8807b31a662f17abea04981956439cc9