28 abr. 2013

Validating R-PLS Sunflower Seed Model (Part 01)

I have ten new sunflower seed samples, with laboratory data and I´m going to use them to validate the performance of a model developed in R with PLS:
Sunflower seed Regressions with "R" - 001
First, I  have a look to the spectra of the validation set (red spectra) compares with the training spectra (blue spectra), without any math treatment applied:

and after, with the MSC applied:

I see clearly some differences, but the idea is to check if the calibration is robust enough to predict the samples according to the statistics we got in the summary of the regression.
In the summary of Sunflower seed Regressions with "R" - 001 , we decide to use 7 terms for our predictions, so:

predict(sflw.g00rmn,ncomp=4,newdata=sflw.msc2.val)

                     G00rmn
171     46.25923
173     53.07202
176     53.48508
177     53.27027
178     46.05511
179     46.73826
180     50.95862
181     52.44956
182     47.59493
183     46.51557

The error is:

Let´s have a look to the "Reference vs Predicted" plot:

predplot(sflw.g00rmn,ncomp=7,newdata=sflw.msc3.val,
asp=1,line=TRUE,col=c("red"))
 


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