Semi-Minimax Estimators of Maxwell Distribution under New Loss Function
Huda Abdullah, Zainab Khalifa
Abstract
Huda Abdullah, Zainab Khalifa
Abstract
In this paper, we obtained some Bayesian estimators of the parameter of Maxwell distribution under New loss function. In order to get a better understanding of our Bayesian analysis, we consider the conjugate prior density, based on a Monte Carlo simulation study. The performance of those estimators have been compared using the mean square error's (MSE's) as the comparison criteria. The result showed that, the Bayesian estimators with Inverted Gamma prior are the best for estimating the scale parameter of Maxwell distribution.
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In this paper, we obtained some Bayesian estimators of the parameter of Maxwell distribution under New loss function. In order to get a better understanding of our Bayesian analysis, we consider the conjugate prior density, based on a Monte Carlo simulation study. The performance of those estimators have been compared using the mean square error's (MSE's) as the comparison criteria. The result showed that, the Bayesian estimators with Inverted Gamma prior are the best for estimating the scale parameter of Maxwell distribution.
Key concepts: Estimator, Minimax, Mathematics, Conjugate prior, Applied mathematics, Mean squared error, Bayesian probability, Prior probability