Neighborhood Mahalanobis distance matrix

Working with the chemometric packages in R help us to understand other chemometric commercial software’s better.

In Resemble we can use the function fDiss to get a matrix of distances between all the samples in a spectra data set, so we get a square and diagonal matrix with zeroes in the diagonal, because the distance between a sample and itself in the PCA space is cero. This way we can see redundant information and remove it from the spectra set. Finally we can get a well distributed cloud of samples and the average spectrum is more representative to all of them.

Here I just trim the matrix in order to see how close the first 10 samples spectra are  between them.
The spectra used was the NIRsoil data from R.