“…where matrix π = [ π
π [1] π
π [2] π
π [3] ], πΏ = [ π
π π π πΌ π½ π
π ], π© = [ β0,25 β0,44 β0,49 0,08 0,05 0,10 0,48 0,51 0,53 0,34 0,43 0,56 0,30 0,24 0,12 β0,17 β0,33 β0,32] , and π πππππ = [ 2,61 2,61 2,61 ] and there are three regression outputs for each tested principal component. Parameters of π
π and π tend to always close each other (redundant) in all principal component scenarios.…”