@article{Gómez2026, 
author = {Héctor W. Gómez and Diego I. Gallardo and Marcelo Bourguignon and Osvaldo Venegas},
title = {EM algorithm in the slashed inverse Rayleigh regression model with an application},
year = {2026},
journal = {AIMS Mathematics},
volume = {11},
number = {7},
pages = {23262-23281},
keywords = {inverse Rayleigh distribution, slash distribution, maximum likelihood, quadratic variance function, EM algorithm},
url = {https://www.sciopen.com/article/10.3934/math.2026938},
doi = {10.3934/math.2026938},
abstract = {This paper introduced a novel distribution that generalized the inverse Rayleigh (IR) distribution. The proposed construction arose from the ratio of two independent random variables: one following the IR distribution and the other a beta distribution. Such a formulation yielded a more flexible model than the baseline IR distribution. We derived key distributional properties, proposed a regression model for the mean, and developed an expectation-maximization (EM) algorithm for maximum likelihood estimation. The finite-sample performance of the estimators was assessed via Monte Carlo simulations, and the practical utility of the model was illustrated through an application to real data.}
}