Pcapro: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
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===Description=== | ===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]]. | |||
====Inputs==== | |||
* '''newdata''' = data to be applied to the existing PCA model | |||
The | * The PCA model, which can be inputs in one of two forms, 1) as a list of input variables, | ||
or 2) as a single model structure variable. These two cases are summarized below: | |||
: | : 1) list of input variables: | ||
: * '''newdata''' = data to be applied to the existing PCA model, ''scaled the same as the original data used to construct the model'' | |||
: * '''loads''' = the model loadings | |||
: * '''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'' ? 1}. | |||
WARNING: Scaling for ''newdata'' should be the same as original data used to create the PCA model! | |||
: 2) 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 pcamod | |||
: and an optional variable ''plots'' which suppresses the plots when set to 0 {default ''plots'' ???}. | |||
NOTE: ''newdata'' will be preprocessed in PCAPRO using information stored in pcamod (pcamod.detail.preprocessing). | |||
====Outputs==== | |||
* '''scoressn''' = the new scores | |||
* '''resn''' = new residuals | |||
* '''tsqn''' = new T<sup>2</sup> values | |||
===See Also=== | ===See Also=== | ||
[[datahat]], [[analysis]], [[explode]], [[modlpred]], [[pca]], [[simca]], [[tsqmtx]] | [[datahat]], [[analysis]], [[explode]], [[modlpred]], [[pca]], [[simca]], [[tsqmtx]] |
Revision as of 14:13, 8 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.
Inputs
- newdata = data to be applied to the existing PCA model
- The PCA model, which can be inputs in one of two forms, 1) as a list of input variables,
or 2) as a single model structure variable. These two cases are summarized below:
- 1) list of input variables:
- * newdata = data to be applied to the existing PCA model, scaled the same as the original data used to construct 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}.
WARNING: Scaling for newdata should be the same as original data used to create the PCA model!
- 2) 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 pcamod
- and an optional variable plots which suppresses the plots when set to 0 {default plots ???}.
NOTE: newdata will be preprocessed in PCAPRO using information stored in pcamod (pcamod.detail.preprocessing).
Outputs
- scoressn = the new scores
- resn = new residuals
- tsqn = new T2 values