On Pitman Closeness of Pitman Estimators

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

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 me...

Tile Pitjian~ of Sfatisflcal Estillators: Latent Years and Tile Renascence

ABSfRACf The Pitman closeness criterion is an intrinsic measure of the comparative behavior of two estimators. based solely on their joint distribution. It generally entails less stringent regulari ty condi tions than in other measures. But. there are some undesirable features of this measure. The past few years have witnessed some developments on Pitman-closeness in its tributaries. and a crit...

Isomorphism of Quadratic Norm and Pc Ordering of Estimators Admitting

BAN estimators generally admit first order representations which insure them to be also asymptotically Pitman closest. For AN estimators admitting a first order representation, an ordering under the Pitman closeness measure is established and is shown to be isomorphic to the one under 'the usual quadratic norm. Multiparameter problems are also treated in the same vein.

Optimality of Blue and Ablue in the Light of the Pitman Closeness of Statistical Estimators

Pitman Closest Estimators Based on Convex Linear Combinations of Two Contiguous Order Statistics

Comparisons of best linear unbiased estimatorswith someother prominent estimators have been carried out over the last six decades since the ground breaking work of Lloyd [13]; see Arnold et al. [1] and David and Nagaraja [9] for elaborate details in this regard. Recently, Pitman closeness comparison of order statistics as estimators for population parameters, such as medians and quantiles, and ...