Comparison of combinatoric and likelihood ratio procedures for classifying samples
A random sample is to be classified as coming from one of two normally distributed populations with known parameters. Combinatoric procedures which classify the sample based upon the sample mean(s) and variance(s) are described for the univariate and multivariate problems. Comparisons of misclassifi...
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Veröffentlicht in: | Communications in statistics. Theory and methods 1982-01, Vol.11 (21), p.2361-2377 |
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Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | A random sample is to be classified as coming from one of two normally distributed populations with known parameters. Combinatoric procedures which classify the sample based upon the sample mean(s) and variance(s) are described for the univariate and multivariate problems. Comparisons of misclassification probabilities are made between the combinatoric and the likelihood ratio procedure in the univariate case and between two alternative combinatoric procedures in the bivariate case. |
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ISSN: | 0361-0926 1532-415X |
DOI: | 10.1080/03610928208828395 |