Parameter estimations of geometric extreme exponential distribution based on dual generalized order statistics

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Abstract

In this study, we consider the maximum likelihood and Bayes esti-mation of the parameters of geometric extreme exponential distribution based on dual generalized order statistics. However, the Bayes esti-mator does not exist in an explicit form for the parameters. We usedan approximation based on Lindley method for obtaining Bayes esti-mates under squared error loss function. We also discuss the asymptotic variance-covariance matrix of maximum likelihood estimators of two pa-rameters. Through Monte Carlo simulation, we compare the maximum likelihood and Bayes estimates of the parameters. And we include one real data analysis.

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Kim, C., Bae, Y. H., & Kim, W. (2016). Parameter estimations of geometric extreme exponential distribution based on dual generalized order statistics. Applied Mathematical Sciences, 10(61–64), 3173–3185. https://doi.org/10.12988/ams.2016.69240

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