On the maximum likelihood estimation in general log-linear models
Methodology
2023-01-02 v2
Abstract
General log-linear models specified by non-negative integer design matrices have a potentially wide range of applications, although using models without the genuine overall effect, that is, ones which cannot be reparameterized to include a normalizing constant, is still rare. The log-linear models without the overall effect arise naturally in practice, and can be handled in a similar manner to models with the overall effect. A novel iterative scaling procedure for the MLE computation under such models is proposed, and its convergence is proved. The results are illustrated using data from a recent clinical study.
Keywords
Cite
@article{arxiv.2208.12024,
title = {On the maximum likelihood estimation in general log-linear models},
author = {Anna Klimova and Matthias Kuhn},
journal= {arXiv preprint arXiv:2208.12024},
year = {2023}
}