Power Lindley Distribution:Different Methods of Estimations and Their Applications to Survival Times Data

摘要

The aim of this paper is to compare through Monte Carlo simulations the finite sample properties of the estimates of the parameters of the power Lindley 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 criteria for comparison. The simulation study concludes that the ordinary and weighted least-squares estimation methods are highly competitive with the maximum likelihood method in small and large samples. This conclusion is also supported with the analysis of two real survival times data sets.