MILES - maximum likelihood fitting for MATLAB

 

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.