Maximum likelihood estimation in the generalized extreme value regression model for binary data
Main Article Content
Generalized extreme value regression model is widely used when the dependent variable Y represents a rare event. The quantile function of the GEV distribution is used as link function to investigate the relationship between the binary outcome Y and a set of potential predictors X. In this article we develop a maximum likelihood estimation procedure int he generalized extreme value regression model. We establish the asymptotic properties (existence, consistency and asymptotic normality) of the proposed maximum likelihood estimator.
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How to Cite
Fatimata, L., Ba, D. B., & Aba, D. (2022). Maximum likelihood estimation in the generalized extreme value regression model for binary data. Gulf Journal of Mathematics, 12(2), 49-56. https://doi.org/10.56947/gjom.v12i2.733