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Consistent estimation of parameters and quantiles of the three-parameter gamma distribution based on Type-II right-censored data
Abstract:In this paper, we propose a method of estimation of parameters and quantiles of the three-parameter gamma distribution based on Type-II right-censored data. In the proposed method, under mild conditions, the estimates always exist uniquely, and the estimators have consistency over the entire parameter space. Through Monte Carlo simulations, we further show that the proposed method performs well compared with another prominent method of estimation in terms of bias and root mean-squared error in small-sample situations. Finally, two real data sets are used for illustrating the proposed method.
Keywords:gamma distribution  maximum likelihood estimation  consistency  existence  uniqueness  bias  mean-squared error  Monte Carlo simulation
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