When we transfer a calibration or a database from one instrument to other, we know in advance that we have a sample presentation error in the instrument where the calibration comes from, and it is important to know it before you interpret the statistics.
In this case I know the predictions from several samples acquired in two repacks, so the sample result we consider is the average, but in this case we are interested in the individual results of every repack (2 results in this case). So I can calculate the difference of both results for every repack and after that (with all the values) I can calculate the standard deviation to get what I can consider the repacking error.
Notice that I will have a value of standard deviation for every parameter.
So I can compare this value with the errors the monitor function gives to me.
The error packaging for the moisture in wheat for a NIR5000 with natural product cell was 0,11. After an standardization to transfer the database to a DS2500 I get an RMSEP error of 0,21, but I can see that maybe due to the samples chosen for the standardization I have an slope which affects specially to the samples with high moisture. But I can see also that the error once than the slope and intercept are corrected is Sres=0,12 , very similar to the repacking error, so there is a good improvement which makes me challenge to try a better standardization to improve the calibration or database transfer.