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iirp

calculates the eigenvectors and the parameters for tuning Independent Interference Reduction (IIR)

Calling sequence

res = iirp(x_ed,xcal,ycal,split,lv,(centering))

Arguments

x_ed:

a matrix (n1 x q) or a Div structure from an experimental design for which y=0 for all observations

xcal,ycal:

calibration dataset; a matrix of spectra (n x q) and a vector of reference values (n x 1) or Div structures

split:

for the cross validation; a scalar representing a number of contiguous blocks, or a vector identifying each observation to a block

lv:

number of latent variables for the PLS regression

(centering):

centred=1 (by default); not centred=0

res.d_matrix:

The D matrix containing only detrimental information, that is x_iirp

res.d_matrix.d is a matrix of dimensions (n1 x q)

res.eigenvec:

eigenvectors of d_matrix

res.eigenvec.d is a matrix of dimensions (q x n_eigenvect)

res.ev_pcent:

eigenvalues of d_matrix in percent

res.ev_pcent.d is a vector of dimensions (n_eigenvect x 1)

res.wilks:

Wilks lambda

res.wilks.d is a vector of dimensions ((n_eigenvect+1) x 1)

not relevant for IIR because only one group

res.rmsecv:

rmsecv for several dimensions of EROS and several dimensions of PLSR

res.rmsecv.d is a matrix of dimensions (lv x (n_eigenvect+1))

res.pls_models:

PLS models obtained after an IIR correction using 0/1/2/...(n_eigenvect) eigenvectors from res.eigenvect.d

res.pls_models is a list of dimensions (n_eigenvect+1)

help pls for more information about the fields of res.pls_models

Examples

[res_iir]=iirp(xg,xcal,ycal,10,5)
[res_iir]=iirp(xg,xcal,ycal,10,5,0)

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