TMPCA Results

Click the OK button in the TMPCA dialog box to display the TMPCA Results dialog box, which contains three tabs: Quick, Plots, and Advanced.

Use the options in this dialog box to review the results of the TMPCA analysis. A wide variety of output in the form of spreadsheets and graphs - including descriptive statistics, predictions, residuals, score, and loading factors - can be generated for the predictor and dependent variables by executing models.

Note: For specific details on next and least significant principal components, R2X and Q2 statistics, and other technical functions mentioned in the option descriptions below, see PCA and PLS Technical Notes.

The Summary box at the top of this dialog box displays the principal components and their properties. Further results can be examined and analyzed using the rest of the options provided in this dialog box.

Element Name Description
Add next Click this button to add the next significant principal component to the PC model. The maximum number of components that can be added to a model is the "number of X variables – 1".
Remove last Click this button to remove the least significant principal component from the PC model.
Remove all Click this button to remove all the principal components from the PC model. By clicking this button, you will effectively delete the model you have built. Nonetheless, you can reconstruct the model via the Add next or Auto-fit more components by cross-validation options on the Results dialog box - Quick tab.
Summary Click this button to generate a summary spreadsheet for the principal components. This output includes the R2X and Q2 statistics, the vector of eigenvalues, number of iterations, and other forms of useful statistics for model interpretation and review.
Cancel Click this button to close the TMPCA Results dialog box and return to the TMPCA Startup dialog box.
Options Click the Options button to display the Options menu.
By Group Click the By Group button to display the By Group specification dialog box.
Code generator If your program is licensed to include this feature, you can generate computer code to implement the current model for predicting new observations. When you click this button, a menu is displayed with the following commands:
PMML script Select this command to generate code in Predictive Model Markup Language (PMML), which is an XML-based language for storing information about fully trained (parameterized) models and for sharing those models with other applications. STATISTICA and STATISTICA Enterprise Server contain facilities to use this information to compute predicted values or classifications, i.e., to quickly and efficiently deploy models (typically in the context of data mining projects). You can also execute saved models in PMML format using the Deployment analysis options in the NIPALS (PCA/PLS) program.
Deployment to STATISTICA Enterprise Select this command to deploy the results as an Analysis Configuration in STATISTICA Enterprise. Note that appropriately formatted data must be available in a STATISTICA Enterprise Data Configuration before the results can be deployed to an Analysis Configuration.