Estimation of mean and its function using asymmetric loss function
Binod Kumar Singh · Zenodo (CERN European Organization for Nuclear Research) · 2013
In this paper suggested an improve estimator for mean using Linex loss function and shows that the improved estimator dominates the Searls (1964) estimator underLinex loss function. The sufficient statistics can be used to find the uniformly minimum risk unbiased estimators. In this paper an improve estimation forµ 2 is suggested (which uses coefficient of variation) under Linex loss function. The mathematical expression of improve estimator of fourth power of mean is also obtained and an improve estimator for common mean in negative exponential distribution is also proposed under Linex loss function.Pandey and Malik (1994) considered the estimator T w x w y w3x y 2 2 2 1 ′ = 1 + + for common mean with the restriction . 1 w1 + w2 + w3 = Here considered the above estimator for 1 w1 + w2 + w3 ≠ and studied its property under Linex loss function. In this paper alsoconsidered the displaced exponential distribution under Linex loss function and suggested an improve estimator.