Estimation of Error Rates by Means of Simulated Bootstrap Distributions |
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Authors: | K.-D. Wernecke G. Kalb |
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Affiliation: | The Humboldt-University of Berlin, GDR Charité Eye Clinic |
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Abstract: | The bootstrap error estimation method is investigated in comparison with the known π-method and with a combined error estimation suggested by us using simulated and normally distributed “populations” in 15 and 30 characters, respectively. For small sample sizes (below the double to threefold number of characters per class) the estimates resulting from the bootstrap method are on the average too small and can no longer be accepted. Significantly better results (with an essentially lower calculation expenditure) are obtained for the π-method and the combined estimation. The variability is essentially the same for all the three methods. This applies both in the case of rather badly separated and in the case of very well separated populations. A bootstrap estimation modified by us also gives unsatisfactory results. |
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Keywords: | Bootstrap method Discriminance analysis Modified bootstrapping Error estimation π-method Combined estimation Simulation |
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