A comparison of several biased estimators for improving the expected error rate of the sample quadratic discriminant function
DOI10.1080/00949658808811057zbMath0726.62092OpenAlexW2135894317MaRDI QIDQ3350531
Linda W. Jennings, Dean M. Young, Roger Peck
Publication date: 1988
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949658808811057
expected error rateprobability of correct classificationrepeated measures analysis of variancecomparison of biased estimatorssample quadratic discriminant functionshrinkage estimators of inverse covariance matrices
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10) Monte Carlo methods (65C05)
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Cites Work
- Estimation of a covariance matrix under Stein's loss
- Estimation of the inverse covariance matrix: Random mixtures of the inverse Wishart matrix and the identity
- Multivariate empirical Bayes and estimation of covariance matrices
- Biased discriminant analysis: Evaluation of the optimum probability of misclassification
- How non-normality affects the quadratic discriminant function
- On the Effects of Dimension in Discriminant Analysis for Unequal Covariance Populations
- The application of bias to discriminant analysis
- Shrunken Estimators in Discriminant and Canonical Variate Analysis
- Discriminant Functions When Covariance Matrices are Unequal
- Discriminant Functions when Covariances are Unequal and Sample Sizes are Moderate
- Further applications of bias to discriminant analysis
- Note on Initial Misclassification Effects on the Quadratic Discriminant Function
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