Minimum Expected Loss Estimators of The Parameters of the Inverse Gaussian Distribution | ||||
| The Egyptian Statistical Journal | ||||
| Article 1, Volume 34, Issue 2, December 1990, Page 260-270 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.1990.315040 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Mohamed Mahmoud | ||||
| Abstract | ||||
| The parameters of the inverse Gaussian distribution are estimated by assuming a weighted squared-error loss function and minimizing the corresponding expected loss with respect to the posterior distribution. These estimators are called minimum expected loss (MELO). We compare the MELO estimators with the corresponding maximum likelihood estimators (MLE) and Bayes estimators using a squared-error loss function (SELO). | ||||
| Keywords | ||||
| Bayes Estimators; Inverse Gaussian Distribution; Maximum Likelihood Estimation; Minimum Expected Loss Estimators; Loss Function | ||||
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