Pitman-Closeness of Preliminary Test and Some Classical Estimators Based on Records from Two-Parameter Exponential Distribution

Abstract: In this paper, we study the performance of estimators of parametersof two-parameter exponential distribution based on upper records. The generalized likelihood ratio (GLR) test was used to generate preliminary test estimator (PTE) for both parameters. We have compared the proposed estimator with maximum likelihood (ML) and unbiased estimators (UE) under mean-squared error (MSE) and Pitman measure of closeness (PMC). Analytical as well as graphical methods are used to show the range of parameter in which PTE performs better than ML and UE. Results demonstrate that in the case of that prior information is not too far from its real value, the PTE is superior in compare with ML and UE based on both MSE and PMC criteria. The results of the paper will be useful in estimation with record data in life testing experiments