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Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves

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  • Peter G. Hall
  • Rob J. Hyndman

    ()

  • Yanan Fan

Abstract

We study methods for constructing confidence intervals, and confidence bands, for estimators of receiver operating characteristics. Particular emphasis is placed on the way in which smoothing should be implemented, when estimating either the characteristic itself or its variance. We show that substantial undersmoothing is necessary if coverage properties are not to be impaired. A theoretical analysis of the problem suggests an empirical, plug-in rule for bandwidth choice, optimising the coverage accuracy of interval estimators. The performance of this approach is explored. Our preferred technique is based on asymptotic approximation, rather than a more sophisticated approach using the bootstrap, since the latter requires a multiplicity of smoothing parameters all of which must be chosen in nonstandard ways. It is shown that the asymptotic method can give very good performance.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2003/wp12-03.pdf
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Bibliographic Info

Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 12/03.

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Length: 14 pages
Date of creation: Jul 2003
Date of revision:
Handle: RePEc:msh:ebswps:2003-12

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Related research

Keywords: Bandwidth selection; binary classification; kernel estimator; receiver operating characteristic curve.;

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Cited by:
  1. Kaushik Ghosh & Ram Tiwari, 2007. "Empirical process approach to some two-sample problems based on ranked set samples," Annals of the Institute of Statistical Mathematics, Springer, vol. 59(4), pages 757-787, December.
  2. Òscar Jordà & Alan M. Taylor, 2011. "Performance Evaluation of Zero Net-Investment Strategies," NBER Working Papers 17150, National Bureau of Economic Research, Inc.

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