Improved estimators for the rate parameter of gamma model using asymptotic properties

In this paper we proposed three estimators namely linear shrinkage, preliminary test and shrinkage preliminary test for the rate parameter of univariate gamma. The salient feature of the proposed estimators is the admissibility property that is defined on belief of the uncertain prior information. Expressions for bias and relative efficiency under method of moment have been derived using asymptotic theory. A Monte Carlo simulation study shows that the proposed estimators are more efficient and minimally biased when prior information is close to the neighbourhood of the rate parameter.