Pcapro

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
• plots = optional variable, which suppresses the plots when set to 0 {default plots = 1}.

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

See Also

datahat, analysis, explode, modlpred, pca, simca, tsqmtx