Estimating Common Scale Parameter of Two Gamma Populations: A Simulation Study
Nadiminti Nagamani, Manas Ranjan Tripathy · American Journal of Mathematical and Management Sciences · 2017
SYNOPTIC ABSTRACTThe problem of estimating the common scale parameter of two gamma populations has been considered when the shape parameters are unknown and possibly different. The performance of an estimator is evaluated using both bias and mean squared error. The maximum likelihood estimator (MLE) has been obtained numerically using the Monte-Carlo simulation, as the closed form does not exist. The Fisher information matrix has been obtained for our model and, consequently, asymptotic confidence intervals have been constructed. Certain Bayes estimators, using various priors, have been obtained. Like the MLE, the closed form of these Bayes estimators does not exist. An approximation due to Lindley (1980 Lindley, D. V. (1980). Approximate bayes method. Trabajos de Estadistica, 31, 223–237.[Crossref] , [Google Scholar]) has been used to obtain these Bayes estimators approximately. Finally, the bias and the mean squared error of all these estimators have been numerically compared through the Monte-Carlo simulation method.