Weihs, Claus and Calzolari, Giorgio and Roehl, Michael C. (1998): Variance reduction with Monte Carlo estimates of error rates in multivariate classification. Published in: Technical Report 44/1999 No. Universitaet Dortmund, SFB 475 (August 1999): pp. 1-12.
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Abstract
In this paper, control variates are proposed to speed up Monte Carlo simulations to estimate expected error rates in multivariate classification.
Item Type: | MPRA Paper |
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Original Title: | Variance reduction with Monte Carlo estimates of error rates in multivariate classification |
Language: | English |
Keywords: | Classification; control variates; error rate; Monte Carlo simulation; variance reduction |
Subjects: | C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling |
Item ID: | 24425 |
Depositing User: | Giorgio Calzolari |
Date Deposited: | 16 Aug 2010 11:48 |
Last Modified: | 03 Oct 2019 04:40 |
References: | [1] R. Y. Rubinstein and B. Melamed, Modern Simulation and Modeling, John Wiley & Sons, 89-97 (1998). [2] G. J. McLachlan, Discriminant Analysis and Statistical Recognition, John Wiley & Sons (1992). [3] I. 0 . Bohachevsky, M. E. Johnson, M. L. Stein, Function Optimization, Technometrics, 28, 3, 209-217 (1986). [4] M. C. Roehl and C. Weihs, Optimal vs. Classical Linear Dimension Reduction, in: W. Gaul, H. Locarek-Junge (eds.), Classification in the Information Age, Studies in Classification, Data Analysis, and Knowledge Organization, Springer, 252-259 (1999). [5] D. M. Young, V. R. Marco and P. L. Odell, Quadratic Discrimination: Some Results on Optimal Low-Dimensional Representation, Journal of Statistical Planning and Inference, 17, 307-319 (1987). [6] J. Lauter, Stabile Multivariate Verfahren, Mathematische Lehrbuecher und Monographien 81, Akademie-Verlag, Berlin (1992). |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/24425 |