Abstract
In this paper, we consider the estimation of the common scale parameter of several Pareto distributions with unknown and unequal shape parameters. This problem often arises in practice, for example, when we have several independent wage distributions each having a Pareto distribution with different shapes but common scale parameter which may be the minimum wage rate. A new class of improved estimators is obtained which dominates the Maximum Likelihood Estimator (MLE) and the Uniformly Minimum Variance Unbiased Estimators (UMVUE) under the Mean Square Error (MSE) and Pitman Nearness. (PN) criterion. Numerical studies indicate the amount of improvements are highly significant.
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