Approximate Bayes Estimation for Log-Dagum Distribution
Abstract
In this article, the approximate Bayes estimation
problem for the log-Dagum distribution with three parameters is considered.
Firstly, the maximum likelihood estimators and asymptotic confidence intervals
based on these estimators for unknown parameters of log-Dagum distribution are
constructed. In addition, approximate
Bayes estimators under squared error loss function for unknown parameters of
this distribution are obtained using Tierney and Kadane approximation. A
Monte-Carlo simulation study is performed to compare performances of maximum
likelihood and approximate Bayes estimators in terms of mean square errrors and
biases. Finally, real data analysis for this distribution is performed.
Keywords
References
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