MILES - maximum likelihood fitting for MATLABTM
by
Rasmus
Bro, Nicholas D. Sidiropoulos & Age K. Smilde
Introduction
MILES
(Maximum likelihood via Iterative Least squares EStimation) is a very simple
principle for fitting maximum likelihood models using simple least squares
algorithms. The principle is described in a recent
paper and an earlier version is also available here.
These
m-files given here provide examples on how to use the MILES principle
specifically for PCA and for PARAFAC. Other models can be fitted equally
simple by exchanging the model-fitting part with any other least squares
algorithm.
Getting the m-files
Read
the information on this page and download the files to your own computer.
If you use the files we would appreciate a reference to
the paper in which MILES is developed.
R. Bro, N. D. Sidiropoulos & A. K. Smilde, Maximum
likelihood fitting using ordinary least squares algorithms, J. Chemom.,
16, 387-400, 2002
If you
have any questions, suggestions or comments please feel free to contact us
at
rb@kvl.dk
Download the files
MILES examples (Updated August, 2001)
Requirements
MATLAB version 5.3 or newer.
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