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imported>Jeremy |
imported>Benjamin |
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| ===Purpose===
| | Working with False-color images, figure 6. |
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| Calculates matrix for T^2+Q contributions for PCA and MPCA.
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| ===Synopsis===
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| :[tsqqmat,tsqqs] = tsqqmtx(x,model,wt)
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| ===Description===
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| ====Inputs====
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| * '''x''' = data matrix [class double or dataset]
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| * '''model''' = PCA or MPCA model standard model struture (see PCA).
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| ====Optional Inputs====
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| * '''wt''' = {sqrt((M-K-1)/(M-1))}, 0<=wt<=1 scalar weighting for contributions 0<wt<1 gives combined T^2 and Q statistics where M is the number of calibration samples and K is the number of PCs.
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| ::wt = 1 gives T^2 and T^2 contributions
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| ::wt = 0 gives standarized Q residuals
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| ====Outputs====
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| * '''tsqqs''' = combined Hotelling's T^2 + Q residual
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| * '''tsqqmat''' = matrix of individual variable contributions such that
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| ::<tt>tsqqs(i) = tsqqmat(i,:)*tsqqmat(i,:)';</tt>
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| ===See Also===
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| [[datahat]], [[pca]], [[pcr]], [[pls]], [[tsqmtx]]
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Revision as of 14:21, 12 May 2017
Working with False-color images, figure 6.
