2005
DOI: 10.51936/tsyr9449
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Robustness of the Fisher's discriminant function to skew-curved normal distribution

Abstract: Discriminant analysis is a widely used multivariate technique with Fisher's discriminant analysis (FDA) being its most venerable form. FDA assumes equality of population covariance matrices, but does not require multivariate normality. Nevertheless, the latter is desirable for optimal classification. To test FDA's performance under non-normality caused by skewness the method was assessed with simulation based on a skew-curved normal (SCN) distribution belonging to the family of skew-generalised normal distribu… Show more

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Cited by 8 publications
(4 citation statements)
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“…Moreover the normality test (Doornik and Hansen 2008) showed a slightly significant value (p=0,045), accounting for a slight departure from normality of the data. Hence the prerequisites to perform DFA were satisfied, since Sever et al (2005) showed the DFA to be highly robust to non-normal data.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Moreover the normality test (Doornik and Hansen 2008) showed a slightly significant value (p=0,045), accounting for a slight departure from normality of the data. Hence the prerequisites to perform DFA were satisfied, since Sever et al (2005) showed the DFA to be highly robust to non-normal data.…”
Section: Resultsmentioning
confidence: 99%
“…Hence the prerequisites to perform DFA were satisfied, since Sever et al (2005) showed the DFA to be highly robust to non-normal data.…”
Section: Comparison Between Tsip Call Of a Pratensis Versus A Spinole...mentioning
confidence: 99%
“…Discriminant analysis determined which of these variables best predicted membership in the straight or gay sample. Previous research found discriminant analysis to be robust when analyzing skewed data ( Sever, Lajovic, & Rajer, 2005 ). The overall χ 2 test was significant, Wilks λ = .734, χ 2 (18) = 70.13, R 2 = .516, p < .…”
Section: Resultsmentioning
confidence: 99%
“…The SGN has been previously used in the literature. In this sense, Sever et al [3] used this model in the context of discriminant analysis; Arnold et al [4] considered the bivariate case; later Gómez et al [5] examined the skew-curved-normal distribution, which is a subfamily of the SGN distribution. The singularity of the Fisher's information matrix was examined by Arellano-Valle et al [6]; in that paper it was concluded that for the SGN model with location and scale parameters, the Fisher information matrix is singular for the particular case when the normality is restored (λ 1 = 0).…”
Section: Introductionmentioning
confidence: 99%