Estimation of parameters of the gamma distribution in the presence of outliers generated from uniform distribution

The maximum likelihood, moment and mixture of the estimators are derived for samples from the gamma distribution in the presence of outliers generated from uniform distribution. These estimators are compared empirically when all the parameters are unknown; their bias and determinants are investigated with the help of numerical technique. We have shown that these estimators are asymptotically unbiased. At the end, we conclude that mixture estimators are better than the maximum likelihood and moment estimators.