Estimating a linear parametric function of a doubly censored exponential distribution. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Tripathi, Yogesh Mani; Petropoulos, Constantinos; Sultana, Farha; Rastogi, Manoj Kumar
• Is Part Of: Statistics. Volume 52:Issue 1(2018)
• Page Start: 99
• Page End: 114
• Publication Date: 2018-01-02
• Subjects: Brewster-Zidek estimator -- censored samples -- inadmissibility -- equivariant estimator; 62C99 -- 62F10; Mathematical statistics -- Periodicals; 519.505
• DOI: 10.1080/02331888.2017.1344242
• Languages: English
• ISSNs: 0233-1888

Abstract

ABSTRACT: For an arbitrary strictly convex loss function, we study the problem of estimating a linear parametric functionμ + k σ, k is a known constant, when a doubly censored sample is available from a two-parameter exponentialE ( μ, σ ) population. We establish the inadmissibility of the best affine equivariant (BAE) estimator by deriving an improved estimator. We provide various implications for quadratic and linex loss functions in detail. Improvements are obtained for the absolute value loss function as well. Further a new class of estimators improving upon the BAE estimator is derived using the Kubokawa method. This class is shown to include some benchmark estimators from the literature.