Pcapro: Difference between revisions
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===Description=== | ===Description=== | ||
This function applies a previously-determined PCA model to a set of new data | This function applies a previously-determined PCA model to a set of new data <tt>newdata</tt>. The PCA model can be input in one of two possible forms: 1) as a list of input variables, or 2) as a single model structure variable that had been previously returned by [[analysis]] or [[pca]]. | ||
For case 1), the scaling for <tt>newdata</tt> should be the same as for the original data used to build the model. For case 2), '''pcapro''' will scale <tt>newdata</tt> based on data contained in <tt>pcamod</tt> | |||
====Inputs==== | ====Inputs==== | ||
: Case 1) model input as a list of variables: | |||
:* '''newdata''' = data to be applied to the existing PCA model, ''scaled the same as the original data used to build the model'' | |||
:* '''loads''' = the model loadings | |||
:* '''ssq''' = the model variance information | |||
:* '''reslm''' = the limit for Q residuals | |||
: * '''newdata''' = data to be applied to the existing PCA model, ''scaled the same as the original data used to | :* '''tsqlm''' = the limit for T<sup>2</sup> | ||
: * '''loads''' = the model loadings | :* '''plots''' = optional variable, which suppresses plotting when set to 0 {default '''plots''' = 1}. | ||
: * '''ssq''' = the model variance information | |||
: * '''reslm''' = the limit for Q residuals | |||
: * '''tsqlm''' = the limit for T<sup>2</sup> | |||
: * '''plots''' = optional variable, which suppresses plotting when set to 0 {default ''plots | |||
: Case 2) model input as a single model structure: | |||
:* '''newdata''' = data to be applied to the existing PCA model, ''in the units of the original data'' | |||
:* '''pcamod''' = the structure variable that contains the PCA model | |||
:* '''plots''' = optional variable, which suppresses the plots when set to 0 {default '''plots''' = 1}. | |||
====Outputs==== | ====Outputs==== |
Latest revision as of 14:35, 10 October 2008
Purpose
Project new data onto an existing principal components model.
Synopsis
- [scoresn,resn,tsqn] = pcapro(newdata,loads,ssq,reslm,tsqlm,plots)
- [scoresn,resn,tsqn] = pcapro(newdata,pcamod,plots)
Description
This function applies a previously-determined PCA model to a set of new data newdata. The PCA model can be input in one of two possible forms: 1) as a list of input variables, or 2) as a single model structure variable that had been previously returned by analysis or pca.
For case 1), the scaling for newdata should be the same as for the original data used to build the model. For case 2), pcapro will scale newdata based on data contained in pcamod
Inputs
- Case 1) model input as a list of variables:
- newdata = data to be applied to the existing PCA model, scaled the same as the original data used to build the model
- loads = the model loadings
- ssq = the model variance information
- reslm = the limit for Q residuals
- tsqlm = the limit for T2
- plots = optional variable, which suppresses plotting when set to 0 {default plots = 1}.
- Case 2) model input as a single model structure:
- newdata = data to be applied to the existing PCA model, in the units of the original data
- pcamod = the structure variable that contains the PCA model
- plots = optional variable, which suppresses the plots when set to 0 {default plots = 1}.
Outputs
- scoressn = the new scores
- resn = new residuals
- tsqn = new T2 values