Qconcalc: Difference between revisions

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===Purpose===
===Purpose===
Calculate Q residuals contributions for predictions on a model.
Calculate Q residuals contributions for predictions on a model.
===Synopsis===
===Synopsis===
:qcon = qconcalc(newx,model)  
:qcon = qconcalc(newx,model)  
:qcon = qconcalc(model);  %requires that model contains residuals
:qcon = qconcalc(model);  %requires that model contains residuals
===Description===
===Description===
Inputs are the new data newx and the 2-way PCA or regression model for which Q contributions should be calculated model.  
 
If the model was created using the "blockdetails = 'all'" option in PLS or PCA (or whatever function was used to create the model), then newx can be omitted to retrieve the Q contributions for the calibration data. Note that this option is not the default so it is unlikely this call will work unless you have specifically created the model with the appropriate call.
This function calculates the Q contributions corresponding to the application of either the original calibration data, or an external set of test data, to a PLS or PCA model.
 
If the model <tt>model</tt> was created using the "blockdetails = 'all'" option in [[pls]] or [[pca]] (or whatever function was used to create the model), then <tt>newx</tt> can be omitted to retrieve the Q contributions for the calibration data used to build the model. Note, however, that this option is not the default option for these functions, so it is unlikely that this call will work unless you have specifically created the model with the appropriate call.
 
====Inputs====
 
* '''newx''' = matrix containing external test data
* '''model''' = structure for the PLS or PCA model to which the data is to be applied
 
====Outputs====
 
* '''qcon''' = matrix of Q contributions for all variables used in '''model''', for all calibration objects, or objects represented in '''newx'''
 
===See Also===
===See Also===
[[datahat]], [[pca]], [[pcr]], [[pls]], [[tconcalc]]
[[datahat]], [[pca]], [[pcr]], [[pls]], [[tconcalc]]

Latest revision as of 14:49, 10 October 2008

Purpose

Calculate Q residuals contributions for predictions on a model.

Synopsis

qcon = qconcalc(newx,model)
qcon = qconcalc(model); %requires that model contains residuals

Description

This function calculates the Q contributions corresponding to the application of either the original calibration data, or an external set of test data, to a PLS or PCA model.

If the model model was created using the "blockdetails = 'all'" option in pls or pca (or whatever function was used to create the model), then newx can be omitted to retrieve the Q contributions for the calibration data used to build the model. Note, however, that this option is not the default option for these functions, so it is unlikely that this call will work unless you have specifically created the model with the appropriate call.

Inputs

  • newx = matrix containing external test data
  • model = structure for the PLS or PCA model to which the data is to be applied

Outputs

  • qcon = matrix of Q contributions for all variables used in model, for all calibration objects, or objects represented in newx

See Also

datahat, pca, pcr, pls, tconcalc