MILES - maximum likelihood fitting for MATLAB
Rasmus Bro, Nicholas D. Sidiropoulos & Age K. Smilde
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 email@example.com
Download the files
MILES examples (Updated August, 2001)
MATLAB version 5.3 or newer.