This is a new video about how to monitor and interpret statistics and graphics for validation. Removing "Y" outliers from Validation SetPrevious videos about the Monitor function  for validation:Should I adjust the Bias?Monitor: Adding "RER" and "...

Chemometric software´s  have the option to export a matrix to a TXT file (in this case a constituents matrix), in a way we can import it easily into R, to work with. It is the first step to go into the R world.I use in this case Win ...

I have developed this exercise with Excel in another post for the same calculations , I am going to develop  it this time with  "R".    edad  long.  peso    mg.kg1    28 &n...

I continue developing the Monitor function in R. The idea is to get statistics which help me to understand the performance of my model.Of course the validation set must be free of outliers (X or Y).I add this time two new statistics: RER and ...

I continue developing the Monitor function. This time a video from  "r twotorials”: “how to access different records within a data frame by using logical tests in r”, gave me the idea to remove the zero values from a data set.When somebody g...

I read in an article that Ian Cowe said that what normally chemometricians do is to look to the graphics, of course interpret those graphics. So I still go on trying to develop a function can help me to understand the graphics and all the statistics th...

A bias or systematic error is quite common when monitoring predictions vs reference data. Anyway we must have certain control limits to decide if the Bias is significant or not. Procedures (as for example ISO 12099 )give details about how to calculate ...

After having a look to this video: http://www.screenr.com/UxH8 from rtwotutorials, and reading some tutorials, I decided to modified the script from the previous post: Practicing Script with “ R”: Monitor , in order to make it more r...

These are  samples analyzed by a reference method (column: Protein) and by an analytical method with a certain model (column: IFTpro). The idea is to create a Monitor Report for some basic statistics (RMSEP, Bias, SEP, R,RSQ) to see how ...

I´ve been practicing after reading a couple of tutorials:R: A self-learn tutorialProgramming in Rto create a basic function  to monitor some  basic statistics as RMSEP, Bias, SEP, Correlation and RSQ. I´ve been doing this with other so...

We have seen in the previous post, how to calculate the correlation spectrum, but other simple way to show  how the bands correlate to the constituent of interest is to calculate R^2. This way we remove the negative part of the correlation spectru...

I treat this matter with other software´s, and of course you can do the same with "R".Once I have the spectra of my samples with a math treatment, I want to draw a correlation spectrum to see which wavelengths have better correlation with the constitu...

In the case of the first derivative for the absortion band, the maximum becomes a cero crossing.Using SG filters, we can calculate it with R, and to see, like in the last posts, the Corrgram matrix.Corrgram for the first derivative for this band:L...

I was working today with "R" to get more patterns with the Corrgram. In the demo raw spectra I wanted this time to look to a band as much Gaussian as possible. I select it and trim the spectra to that region treated with the MSC ("Multiple Scatter Corr...

With the "Corrgram" package we can see patterns that can help us to recognize possible inter-correlations in a big matrix. This could be the case to see the correlation to every wavelength respect to all others. This way we can see the high correlation...

Thanks a lot to Kevin W., for his comment in my previous post.Corrgram, it a nice package and I found very nice information to understand it a little bit better on Internet apart from the R help page.Corrgrams: Exploratory displays for correlation matr...

It is important to understand as better as possible our sample set before to develop the regression. Continuing with the “Y” matrix (constituent’s matrix) we have to observe the correlation matrix.In the R Graph Gallery, we can get the code to dr...

From the previous post, we can make the difference spectrum (once the samples are sorted by moisture) between the sample with the lowest moisture value (position 1), from the sample with the highest moisture value (position 66). This spectra will help ...

I use to see the videos from:http://www.twotorials.com/and the video:How to order and sort stuff in Ris really useful to apply this concept to organize and understand better our sample sets before to proceed to develop a calibration.The idea of this po...

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