TMPCA - Fitting Tab

Select the Fitting tab of the TMPCA dialog box to access the options described here.

Note: For specific details on V-fold and Krzanowski cross-validation, Q2X, and other technical functions mentioned in the option descriptions below, see PCA and PLS Technical Notes.
Element Name Description
Fitting method The following options are available in the Fitting method group box:
Number of components by cross-validation When this option button is selected, STATISTICA will determine the complexity of the TMPCA model, i.e., the optimal number of principal components using the method of cross-validation. The "optimal number" is defined as the number of principal components that achieves the best goodness of prediction Q2X. STATISTICA selects the optimal model complexity using either the method of V-fold or Krzanowski cross-validation.
Fixed number of components Select this option button to extract a fixed number of components from the data. Enter the number in the adjacent box. Note that principal components with values of significance falling below a threshold will still be ignored.
Minimum eigenvalue limit Select this option button to extract all principal components with eigenvalues greater than the value specified in the adjacent box. Principal components with eigenvalues less than the specified value will be considered as insignificant and will be excluded from the model.
Cross-validation specifications Use the options in this group box to specify the cross-validation type to be used for selecting the number of principal components (model complexity). For V-fold cross-validation, you can also determine the number of folds and seed value for the random number generator.
V-fold Select this option button to use the standard V-fold cross-validation for determining the optimal number of principal components.
Krzanowski Select this option button to use the Krzanowski cross-validation for determining the optimal number of principal components.
Off Select this option button if you do not want to use cross-validation for determining the optimal number of principal components. Available only when the fitting method is either Fixed number of components or Minimum eigenvalue limit.
V-fold The following options are in the V-fold group box.
V value Use this box to specify the number of cross-validation folds.
Seed The positive integer value entered here is used as the seed for a random number generator that produces v independent random samples.