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تحلیل تبعیضی خطی (LDA×تحلیل واریانس چندمتغیره (MANOVA)×
حوزهآمارآمار
خانوادهHypothesis testHypothesis test
سال پیدایش19361932
پدیدآورRonald A. FisherSamuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)
نوعParametric linear classifier / dimensionality reductionParametric multivariate mean comparison
منبع بنیادینFisher, R.A. (1936). The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics, 7(2), 179–188. DOI ↗Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
نام‌های دیگرLDA, Fisher's LDA, Fisher's linear discriminant, discriminant function analysisMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)
مرتبط75
خلاصهLinear Discriminant Analysis (LDA) is a parametric supervised classification method that finds the linear combination of continuous predictors that best separates two or more predefined groups. Introduced by Ronald A. Fisher in his landmark 1936 paper on taxonomic measurements, it simultaneously serves as a classifier and a dimensionality-reduction tool, and can be understood as the classification-oriented counterpart of MANOVA.MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932.
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ScholarGateمقایسهٔ روش‌ها: Linear Discriminant Analysis (Classification) · MANOVA. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare