Depth-Based Recognition of Shape Outlying Functions

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10365500" target="_blank" >RIV/00216208:11320/17:10365500 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1080/10618600.2017.1336445" target="_blank" >http://dx.doi.org/10.1080/10618600.2017.1336445</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/10618600.2017.1336445" target="_blank" >10.1080/10618600.2017.1336445</a>

Result language
angličtina
Original language name
Depth-Based Recognition of Shape Outlying Functions
Original language description
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.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA14-07234S" target="_blank" >GA14-07234S: Multivariate regression quantiles in econometrics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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