MILES - maximum likelihood fitting for MATLAB. 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. (Source: http://plato.asu.edu)
References in zbMATH (referenced in 1 article )
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- Yaser Samadi, S.; Billard, L.; Meshkani, M. R.; Khodadadi, A.: Canonical correlation for principal components of time series (2017)