Documentation and Faq how are T contributions calculated: Difference between pages
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===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. | |||
[[Category:FAQ]] | |||
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.