search for: gw_obj

...th a composite signature (of metals "Al","Sb","Bi","Cr","Ba") capable of discriminating 100% of the source factors (LANDUSE: "A","B","C"). The Wilks' lambda portion seems straightforward. I am using the following: gw_obj <- greedy.wilks(LANDUSE ~ ., data = QRBdfa, niveau = 0.1) gw_obj Thus determining the stepwise order of metals.But I can't seem to figure out how to coerce the DFA to give me an output with the % of factors which each successive metal (variable) correctly classifies (discriminates). e.g. S...

....77 ... $ I030N2: num 7.19 27.25 25.28 100 2.68 ... $ I031N2: num -100 -100 8.989 -100 0.598 ... $ I032N2: num 75.4 67 59 0 95.2 ... $ I033N2: num 17.45 5.74 6.74 100 1.49 ... $ I034N2: num 0.472 0.815 0.482 0.399 1.557 ... $ I035N2: num 0 1 100 100 100 100 100 100 0 100 ... > gw_obj <- greedy.wilks(gruppo~., data = data_indiciN2,niveau = 0.1) Errore in summary.manova(e2, test = "Wilks") : residuals have rank 2 < 3 -- View this message in context: http://r.789695.n4.nabble.com/Stepwise-Discriminant-Analysis-greedy-wilks-tp4633902.html Sent from the R help mai...

...19.68 1.77 ... $ I030N2: num 7.19 27.25 25.28 100 2.68 ... $ I031N2: num -100 -100 8.989 -100 0.598 ... $ I032N2: num 75.4 67 59 0 95.2 ... $ I033N2: num 17.45 5.74 6.74 100 1.49 ... $ I034N2: num 0.472 0.815 0.482 0.399 1.557 ... $ I035N2: num 0 1 100 100 100 100 100 100 0 100 ... > gw_obj <- greedy.wilks(gruppo~., data = data_indiciN2,niveau = 0.1) Errore in summary.manova(e2, test = "Wilks") : residuals have rank 2 < 3 -- View this message in context: http://r.789695.n4.nabble.com/greedy-wilks-tp4633897.html Sent from the R help mailing list archive at Nabble.c...