opa {alsace} | R Documentation |
This function finds the set of most dissimilar rows in a data matrix. If no initial selection is presented, the first object is selected by comparison with the vector of column means. As a distance function the determinant of the crossproduct matrix is used.
opa(x, ncomp, initXref = NULL)
x |
Data matrix (numerical). May not contain missing values. |
ncomp |
Number of rows to be selected. |
initXref |
Optional matrix to be expanded - should be a subset of the rows to select. |
The function returns a submatrix of X, where the columns contain the (unit-length scaled) spectra from the input data that are most dissimilar.
Ron Wehrens
F. Questa Sanchez et al.: Algorithm for the assessment of peak purity in liquid chromatography with photodiode-array detection. Analytica Chimica Acta 285:181-192 (1994)
R. Wehrens: Chemometrics with R. Springer Verlag, Heidelberg (2011)
data(tea) tea <- lapply(tea.raw, preprocess, maxI = 100) ncomp <- 7 spectra <- opa(tea, ncomp) myPalette <- colorRampPalette(c("black", "red", "blue", "green")) mycols <- myPalette(ncomp) matplot(as.numeric(rownames(spectra)), spectra, type = "l", lty = 1, xlab = expression(lambda), ylab = "", col = mycols) legend("topright", legend = paste("Comp.", 1:ncomp), col = mycols, lty = 1, ncol = 2, bty = "n")