The Maximum Likelihood Degree of Farlie Gumbel Morgenstern Bivariate Exponential Distribution
Pooja Yadav, Tanuja Srivastava
TL;DR
This paper investigates the maximum likelihood degree of the Farlie-Gumbel-Morgenstern bivariate exponential distribution, analyzing the number of solutions to the likelihood equations over complex numbers.
Contribution
It provides the first detailed analysis of the maximum likelihood degree for this specific bivariate exponential distribution.
Findings
Determined the maximum likelihood degree for the distribution.
Identified conditions under which the likelihood equations have multiple solutions.
Contributed to the understanding of the algebraic complexity of the model.
Abstract
The maximum likelihood degree of a statistical model refers to the number of solutions, where the derivative of the log-likelihood function is zero, over the complex field. This paper examines the maximum likelihood degree of the parameter in Farlie-Gumbel-Morgenstern bivariate exponential distribution.
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Taxonomy
TopicsStatistical Distribution Estimation and Applications · Bayesian Methods and Mixture Models · Advanced Statistical Methods and Models