An approach to structure determination and estimation of hierarchical Archimedean Copulas and its application to Bayesian classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F15%3A%230003540" target="_blank" >RIV/47813059:19520/15:#0003540 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/16:00442862
Result on the web
<a href="http://link.springer.com/article/10.1007/s10844-014-0350-3" target="_blank" >http://link.springer.com/article/10.1007/s10844-014-0350-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10844-014-0350-3" target="_blank" >10.1007/s10844-014-0350-3</a>

Result language
angličtina
Original language name
An approach to structure determination and estimation of hierarchical Archimedean Copulas and its application to Bayesian classification
Original language description
Copulas are distribution functions with standard uniform univariate marginals. Copulas are widely used for studying dependence among continuously distributed random variables, with applications in finance and quantitative risk management; see, e.g., thepricing of collateralized debt obligations. The ability to model complex dependence structures among variables has recently become increasingly popular in the realm of statistics, one example being data mining (e.g., cluster analysis, evolutionary algorithms or classification). The present work considers an estimator for both the structure and the parameters of hierarchical Archimedean copulas. Such copulas have recently become popular alternatives to the widely used Gaussian copulas. The proposed estimator is based on a pairwise inversion of Kendall's tau estimator recently considered in the literature but can be based on other estimators as well, such as likelihood-based. A simple algorithm implementing the proposed estimator is provi
Czech name
—
Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Project
<a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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