ZELINKA, Jiří. Kernel Estimates of ROC Curves. In Compstat 2008, Books of Abstracts. Porto: IASC, 2008, p. 249-249. ISBN 978-972-95396-3-3.
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Basic information
Original name Kernel Estimates of ROC Curves
Name in Czech Jádrové odhady ROC křivek
Authors ZELINKA, Jiří (203 Czech Republic, guarantor).
Edition Porto, Compstat 2008, Books of Abstracts, p. 249-249, 1 pp. 2008.
Publisher IASC
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10103 Statistics and probability
Country of publisher Portugal
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14310/08:00027285
Organization unit Faculty of Science
ISBN 978-972-95396-3-3
Keywords in English kernel estimate; ROC curve; bandwidth
Tags bandwidth, kernel estimate, ROC curve
Tags International impact
Changed by Changed by: Mgr. Jiří Zelinka, Dr., učo 72. Changed: 9/1/2009 11:39.
Abstract
ROC curves are important tool for comparing diagnostic tests. Nonparametric kernel estimation is useful in the case when no information about the distribution of the data is available. Presented contribution is focused on the method of kernel estimate of ROC curve as a special type of cumulative distribution function. This approach can be applied for choice of smoothing parameter called bandwidth and also for evaluation of area under ROC curve (AUC) or partial AUC. Suggested method is compared with another methods and it is tested on simulated and real data.
Abstract (in Czech)
ROC křívky jsou důležitým parametrem pro porvnání diagnostických testů. Neparametrické jádrové odhady jsou užitečné pro jejich konstrukci, pokud nemáme k dispozici informaci o rozložení testovaných veličin. Metoda navržená v příspěvku je vhodná pro odhad šířky vyhlazovacího okna, která je nejdůležitějším parametrem při jádrovém vyhlazování.
Links
LC06024, research and development projectName: Centrum Jaroslava Hájka pro teoretickou a aplikovanou statistiku
Investor: Ministry of Education, Youth and Sports of the CR, Jaroslav Hájek Center for Theoretical and Applied Statistics
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