The MVPMODEL Procedure
Output Data Sets
OUT= Data Set
The OUT= data set contains all the variables in the input data set plus new variables that contain the principal component scores, residuals, and other computed values listed in Table 12.2.
The names of the score variables are formed by concatenating the value given by the PREFIX= option (or the default Prin, if PREFIX= is not specified) and the numbers 1, 2, …, j, where j is the number of principal components in the model.
The names of the residual variables are formed by concatenating the value given by the RPREFIX= option (or the default R_, if RPREFIX= is not specified) and the names of the process variables used in the analysis. Residual variables are created
only when the number of principal components in the model is less than the number of process measurement variables in the
input data set.
Table 12.2: Computed Variables in the OUT= Data Set
|
Variable |
Description |
|---|---|
|
Prin1–Prinj |
Principal component scores |
|
R_ |
Residuals |
|
_NOBS_ |
Number of observations used in the analysis |
|
_SPE_ |
Squared prediction error (SPE) |
|
_TSQUARE_ |
|
OUTLOADINGS= Data Set
The OUTLOADINGS= data set contains the eigenvalues of the correlation (or covariance) matrix, the loadings computed for the process variables, and other information about the principal component model. The variables that are saved in the OUTLOADINGS= data set are listed in Table 12.3.
Table 12.3: Variables in the OUTLOADINGS= Data Set
|
Variable |
Description |
|---|---|
|
_VALUE_ |
Character variable identifying the type of values in an observation |
|
_PC_ |
Principal component number |
|
_NOBS_ |
Number of observations used in the analysis |
|
process variables |
Eigenvalues, means, standard deviations, and loadings for process variables |
Valid values for the _VALUE_ variable are as follows:
- EIGEN
-
eigenvalues from the principal component analysis
- LOADING
-
principal component loadings
- MEAN
-
process variable means
- STD
-
process variable standard deviations
For an observation where _VALUE_ is equal to LOADING, the _PC_ variable identifies the principal component whose loadings are recorded in that observation.
The process variable means and standard deviations are used by the other MVP procedures to center and scale new data in a Phase II analysis. If you specify the NOCENTER option, the OUTLOADINGS= data set does not contain a MEAN observation. If you specify the NOSCALE option, the OUTLOADINGS= data set does not contain a STD observation.