Bayesian Analysis for the Modified Frechet–Exponential Distribution with Covid-19 Application
Abstract
In this manuscript, the maximum likelihood estimators and Bayes estimators for the parameters of the modified Frechet–exponential distribution. Because the Bayes estimators cannot be obtained in closed forms, the approximate Bayes estimators are computed using the idea of Lindley’s approximation method under squared-error loss function. Then, the approximate Bayes estimates are compared with the maximum likelihood estimates in terms of mean square error and bias values using Monte Carlo simulation. Finally, real data sets belonging to COVID-19 death cases in Europe and China to are used to demonstrate the emprical results belonging to the approximate Bayes estimates, the maximum likelihood estimates.
Keywords
Modified Frechet–Exponential distribution, Bayes estimator, Lindley’s approximation, Monte Carlo simulation, Squared-error loss function.
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