Simcasub: Difference between revisions

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*'''''options''''' =  a structure array. This is the same as PCA.
*'''''options''''' =  a structure array. This is the same as PCA.


===Output===
====Output====


* '''model''' = a PCA model
* '''model''' = a PCA model

Latest revision as of 06:08, 17 September 2018

Purpose

simcasub calculates a single SIMCA Sub-model.

Synopsis

model = simcasub(x,modelclasses,ncomp,options); %identifies model (calibration)

Description

simcasub calculates a single SIMCA sub-model for inclusion into a SIMCA model. A SIMCA sub-model is a PCA model built only on samples of a given class (or classes) as identified in a DataSet object's class{1} field. Inputs are identical to PCA except a second input (modelclasses) follows the x-block specifying which class or classes on which the sub-model should be built. (modelclasses) is a scalar or a vector of classes.

NOTE: simcasub is not the usual route to perform SIMCA predictions - use PCA to do predictions from a SIMCA sub-model or SIMCA to do predictions from a SIMCA model.

Input

  • x = M x N matrix of class "dataset" where class information is extracted from x.class{1,1} and labels from x.label{1,1}.
  • modelclasses = M x 1 vector of class identifiers where each element is an integer identifying the class number of the corresponding sample.

Optional Inputs

  • ncomp = integer, number of PCs to use in each model. This is rarely known a priori. When ncomp=[] {default} the user is querried for number of PCs for each class.
  • options = a structure array. This is the same as PCA.

Output

  • model = a PCA model

See Also

pca, plsda, simca