Weighted Exponential Distribution: Different Methods of Estimations

The aim of this paper is to compare through Monte Carlo simulations the finite sample properties of the estimates of the parameters of the weighted exponential distribution obtained by five estimation methods: maximum likelihood, moments, L-moments, ordinary least-squares, and weighted least-squares. The bias and mean-squared error are used as the criterion for comparison. The simulation study concludes that the last four estimation methods perform well and are highly competitive with the maximum likelihood method in small and large samples. This conclusion is also supported with the analysis of two real data sets.