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...ad(...) #L v D L=data[LvD %in% c("L"),] D=data[LvD %in% c("D"),] #Groups 3 and 4 within L and D group3L=L[group %in% c("3"),] group4L=L[group %in% c("3"),] group3D=D[group %in% c("3"),] group4D=D[group %in% c("3"),] #Times B, S45, FR2, FR8 you get the idea Is there a more efficient way to subset groups? Thanks for any insight. Regards, Charles [[alternative HTML version deleted]]

...th R2 and Q2 but they are for each separate class. Is there a way to get the cumulative R2 and Q2 for the whole model? R2(pls.new, estimate="all") Response: B (Intercept) 1 comps 2 comps train 0.00000 0.001759 0.3812 CV -0.03419 -0.082686 0.2983 Response: FR8 (Intercept) 1 comps 2 comps train 0.00000 0.4362 0.4362 CV -0.03419 0.3936 0.3745 Response: S45 (Intercept) 1 comps 2 comps train 0.00000 0.3682 0.7749 CV -0.03419 0.3061 0.7313 Again, what I am looking for is a way to get an overall R2 an...

...th R2 and Q2 but they are for each separate class. Is there a way to get the cumulative R2 and Q2 for the whole model? R2(pls.new, estimate="all") Response: B (Intercept) 1 comps 2 comps train 0.00000 0.001759 0.3812 CV -0.03419 -0.082686 0.2983 Response: FR8 (Intercept) 1 comps 2 comps train 0.00000 0.4362 0.4362 CV -0.03419 0.3936 0.3745 Response: S45 (Intercept) 1 comps 2 comps train 0.00000 0.3682 0.7749 CV -0.03419 0.3061 0.7313 Again, what I am looking for is a way to get an overall R2 an...

...var #this provides the exact R2Y I get in SIMCAP pls.reg.new$Q2cum The Q2cum values should be close to component 1 = .2149 component 2 = .4578 *component 3 = .6627* #value of concern All of the R output values are close for the respective class except for the final Q2cum value: Q2cum.B Q2cum.FR8 Q2cum.S45 Q2cum t1 -0.0546 0.3992 0.2973 0.2140 t2 0.2863 0.3824 0.7039 0.4573 t3 0.5839 0.7430 0.6980 *0.3735 *#*not close* Done. I have read that the plspm package used LOO cross validation. SIMCAP uses the same method, however it le...

...xpvar? #this provides the exact R2Y I get in SIMCAP pls.reg.new$Q2cum The Q2cum values should be close to component 1 = .2149 component 2 = .4578 component 3 = .6627 #value of concern All of the R output values are close for the respective class except for the final Q2cum value: ?? Q2cum.B Q2cum.FR8 Q2cum.S45? Q2cum t1 ?? -0.0546?? ? ?? 0.3992?? ? ?? 0.2973 ? 0.2140 t2???? 0.2863? ? ? ? 0.3824?? ? ?? 0.7039?? 0.4573 t3 ? ? 0.5839??????? 0.7430? ? ? ? 0.6980?? 0.3735? #not close Done. I have read that the plspm package used LOO cross validation.? SIMCAP uses the same method, however it leaves...

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