Download User Guide to

Transcript
User Guide to SIMCA
Vector
Description
Displayed
matrix Uo is not completely orthogonal to X.
The norm of this matrix is usually very small
but is used to enhance the predictions of X.
Available for OPLS and O2PLS.
R2VX
Explained fraction of the variation of the X
variables, for the selected component.
Home | Summary
of fit | Component
contribution
R2VXAdj
Explained fraction of the variation of the X
variables, adjusted for degrees of freedom,
for the selected component.
Home | Summary
of fit | Component
contribution
R2VXAdjc
um
Cumulative explained fraction of the variation
of the X variables, adjusted for degrees of
freedom.
Home | Summary
of fit | X/Y overview
R2VXcum
Cumulative explained fraction of the variation
of the X variables.
Home | Summary
of fit | X/Y overview
R2VY
Explained fraction of the variation of the Y
variables, for the selected component.
Home | Summary
of fit | Component
contribution
R2VYAdj
Explained fraction of the variation of the Y
variables, adjusted for degrees of freedom,
for the selected component.
Home | Summary
of fit | Component
contribution
R2VYAdjc
um
Cumulative explained fraction of the variation
of the Y variables, adjusted for degrees of
freedom.
Home | Summary
of fit | X/Y overview
R2VYcum
Cumulative explained fraction of the variation
of the Y variables.
Home | Summary
of fit | X/Y overview
RMSEcv
Root Mean Square Error, computed from the
selected cross validation round.
Analyze | RMSECV
RMSEE
Root Mean Square Error of the Estimation
(the fit) for observations in the workset.
RMSEP
Root Mean Square Error of the Prediction for
observations in the predictionset.
Predict | Y PS |
Scatter
Predict | Y PS |
Line
S2VX
Residual variance of the X variables, after
the selected component, scaled as specified
in the workset.
S2VY
Residual variance of the Y variables, after
the selected component, scaled as specified
in the workset.
so
So is the projection of to onto Y.
So contains non-zero entries when the score
matrix To is not completely orthogonal to Y.
The norm of this matrix is usually very small
506
Home | Loadings |
Orth X