Integrated data depth for smooth functions and its application in supervised classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10314013" target="_blank" >RIV/00216208:11320/15:10314013 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/article/10.1007%2Fs00180-015-0566-x" target="_blank" >http://link.springer.com/article/10.1007%2Fs00180-015-0566-x</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00180-015-0566-x" target="_blank" >10.1007/s00180-015-0566-x</a>

Result language
angličtina
Original language name
Integrated data depth for smooth functions and its application in supervised classification
Original language description
This paper concerns depth functions suitable for smooth functional data. We suggest a modification of the integrated data depth that takes into account the shape properties of the functions. This is achieved by including a derivative(s) into the definition of the suggested depth measures. We then further investigate the use of integrated data depths in supervised classification problems. The performances of classification rules based on different data depths are investigated, both in simulated and realdata sets. As the proposed depth function provides a natural alternative to the depth function based on random projections, the difference in the performances of these two methods are discussed in more detail.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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