Publications by jrcuesta

NIT: Fatty acids study in R – Part 007

14.03.2012

Once we have chosen the model, we can continue acquiring spectra of new samples. Spectra is exported to a txt or csv file and we imported in R to be reprocessed.We use the function “predict” from the PLS package. I have done this with 20 new samples. We need first to apply to them the adequate math treatment (same as the used in the model). I...

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Savitzky-Golay filters in R

17.03.2012

Derivatives are a good way to extract information to our spectra. As we know NIR contents overlapping bands, and spectra must be treated with math operations in order to extract as much information as possible and to correlate it with the constituent  of interest in the case of quantitative analysis or to discriminate two similar products.Deriva...

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Applying Savitzky-Golay filters in “R”

20.03.2012

When applying SG, we select a moving average window with an odd value “n” for the number of data points. SG fit a polynomial of “p” degree to this data points and give the value to the central point (this is the reason to have an odd value). We apply also an smooth in the case of “m” = 0, or the first (m=1), second (m=2) or third (m=3...

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VIDEO:Looking to "NIR" Spectra in "R": (Import and organize)

24.03.2012

Related To leave a comment for the author, please follow the link and comment on their blog: NIR-Quimiometría. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job. Want to share your content on R-bloggers? click here ...

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VIDEO: Applying "MSC" math-treatment to our raw spectra in "R".

25.03.2012

Related To leave a comment for the author, please follow the link and comment on their blog: NIR-Quimiometría. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job. Want to share your content on R-bloggers? click here ...

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VIDEO: Applying "SNV" math-treatment to our raw spectra in "R".

26.03.2012

Related To leave a comment for the author, please follow the link and comment on their blog: NIR-Quimiometría. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job. Want to share your content on R-bloggers? click here ...

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SCRIPT for NIR "DEMO" Tutorial – 001

28.03.2012

########### RAW NIR Demo Data##################################demoVISVISNIRNIRALLALLProteinFatAshDMMoisturedemo_raw+ Moisture=I(Moisture),VIS=I(VIS),NIR=I(NIR),ALL=I(ALL))wave_viswave_nirwave_allmatplot(wave_vis,t(demo_raw$VIS),lty=1,pch=”.”,xlab=”nm”,ylab=”log(1/R)”)matplot(wave_nir,t(demo_raw$NIR),lty=1,pch=”.”,xlab=”nm”,yl...

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Dividing the Sample Set in two (Validation & Training)

29.03.2012

We have in the Demo sample set “66” samples.  In this post we´ll see one way to divide the set in two parts: one for “Validation” and another for Training or Calibration.The selection will be random. And we are going to use the command: “sample”. I decided to select 10 samples for validation, and the rest for training.demo_raw_valIf...

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Comparing Spectra with different math treatments

30.03.2012

It is amazing the quantity of graphics you can develop with R, and how you can show and manage  these graphics. Here in the same plot we compare the raw demo spectra, treated with MSC, SNV and with the first derivative (differences between consecutive  data points). We can see how SNV and MSC look similar, but if you look to the Y  axis, they ...

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VIDEO: "R" Checking the reference values ("Y" Matrix).

30.03.2012

Related To leave a comment for the author, please follow the link and comment on their blog: NIR-Quimiometría. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job. Want to share your content on R-bloggers? click here ...

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