Building Models Quick Start and Faq how are T contributions calculated: Difference between pages

From Eigenvector Research Documentation Wiki
(Difference between pages)
Jump to navigation Jump to search
imported>Scott
No edit summary
 
imported>Lyle
(Created page with "===Issue:=== How are T-contributions calculated? ===Possible Solutions:=== In PCA, T-contributions represent how the original variables contribute to give each sample its T...")
 
Line 1: Line 1:
{| border="1" cellpadding="5" cellspacing="0" align="left"
===Issue:===
|-
|width="20%" valign="top" |
* Once data has been loaded into the workspace, there are several ways to begin building a model.  For analysis tools like PCA where only an '''X''' block is required, you can right-click on the data icon in the '''Browser''' to reveal a list of analysis options. You can also drag the given data to an analysis method shortcut, such as the Decompose '''PCA''' shortcut.
|width="80%" | [[Image:build_model.003.png]]
|-
|valign="top"|
* The Analysis GUI will then appear with the given data already loaded. (The large '''X''' (block) button in the Analysis GUI will appear depressed indicating the data is loaded - passing the cursor over the button will provide a summary of the '''X''' block data.)
|:[[Image:build_model.004.png]]
|-
|valign="top"|
* While each analysis type has its own nuances, in general the steps to build a model are:
** load the data
** view the data
** choose preprocessing
** select the type of cross-validation to use (if any is desired - see [[Using Cross-Validation]])
** build the model
** review the model


* There is more than one way to accomplish each of the above steps.  For example, preprocessing can be set for the '''X''' block by
How are T-contributions calculated?
** clicking the '''"Choose Preprocessing"''' button in the Analysis Flowchart
** clicking the '''P''' button next to the '''X''' button
** select '''"Preprocess"''' menu item


('''Hint:''' Once selected, use the Preprocess/X-block and Preprocess/Y-block menus to save the current preprocessing as the default.)
===Possible Solutions:===


* You can quickly view your data by right-clicking on the appropriate button ('''X''' or '''Y''') and then select '''"Plot Data"'''
In PCA, T-contributions represent how the original variables contribute to give each sample its T^2 value in a given model. They are calculated as if you are reconstructing the data (relative to the mean of the calibration data) except that each factor is first normalized by the variance it captured in the original data. This gives the reconstruction of the data as if all principal components captured equal amounts of variance in the original data. In other words: this is how the original variables project into the normalized multivariate space of the model.


|:[[Image:build_model.005.png]]
To calculate the T-contributions for a given sample in a PLS_Toolbox PCA model, use the tconcalc function. Given the sample's data in variable data and the model in variable model, the following will calculate T-contributions.  
|-
|valign="top"|
* Perhaps the quickest way for new users to complete the remaining steps to build the model is to use the flowchart.
|[[Image:build_model.006.png]]


|}
[[Category:FAQ]]
[[Review Results Quick Start | Next Topic: Review Results]]

Revision as of 08:57, 21 November 2018

Issue:

How are T-contributions calculated?

Possible Solutions:

In PCA, T-contributions represent how the original variables contribute to give each sample its T^2 value in a given model. They are calculated as if you are reconstructing the data (relative to the mean of the calibration data) except that each factor is first normalized by the variance it captured in the original data. This gives the reconstruction of the data as if all principal components captured equal amounts of variance in the original data. In other words: this is how the original variables project into the normalized multivariate space of the model.

To calculate the T-contributions for a given sample in a PLS_Toolbox PCA model, use the tconcalc function. Given the sample's data in variable data and the model in variable model, the following will calculate T-contributions.