Publications by jrcuesta
Practicing Script with “ R”: Monitor
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 well the model performs.Sample Protein IFTpro 3 12.85 12.954 12.68 12.59...
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Improving script_001: “Monitor”
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 robust .If there are NA values in our X and Y variables, the results for all the statistics will be NA (see a...
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Should I adjust the Bias?
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 the Bias Control Limits (BCL). The idea is a “T test” to calculate if the differences betwe...
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Improving script_002: “Monitor”
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 there are behind.I add some more lines to the monitor function:plot(x~y,main=”X-Y plot”,xlab=�...
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Monitor: Removing zero values from the data set.
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 give you a table like the one I show, if the laboratory did not analyze a sample for any reason, I ...
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Monitor: Adding "RER" and "RPD" statistics
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 RPD.These statistics must be treated with caution, because depends of the range, standard deviation an...
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Mahalanobis distance with "R" (Exercice)
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 31 130.0 68.122 24 28 143.0 127.893 28 20 136.0 89.034 32 34 130.5 ...
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Exporting from Win ISI / Importing into R
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 ISI Software, but sure you can do it with othersoftware´s as well.See the video:Exporting from Wi...
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Removing "Y" outliers from the "Validation Set"
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 “RPD” statisticsOther posts with part of the script:Monitoring some statistic...
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F-test to find UECLs
I have fixed the link to the video “Removing Y outliers from the validation set” and it´s time to see what could be the next step to the function. As we know the RMSEP is the sum of the explained (BIAS) and unexplained error (SEP). We get also the SEP, so we know the unexplained error, and we can compare bouth in order to see if the Bias is ...
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