"Approximation for The Expectation of A Function of The Sample Mean" by Rasul A. Khan
 

Document Type

Article

Publication Date

2004

Publication Title

Statistics

Abstract

Let X¯ n be the mean of a random sample of size n from a distribution with mean μ and variance σ2. Under some conditions it is shown that Ef(X¯ n ) = f(μ) + (σ2/2n) f″(μ) + O(n −2), and var(f(X¯ n )) = (σ2/n) (f′(μ))2 + O(n −2), where f is a continuous function with a suitable growth condition. This complements a result of Lehmann [(1991). Theory of Point Estimation. Wadsworth, California] and Cramér [(1946). Mathematical Methods of Statistics. Princeton University Press, Princeton, N.J.] for wider application. An illustrative example is given to show an application where the usual approximations do not apply.

DOI

10.1080/02331880310001655635

Version

Postprint

Volume

38

Issue

2

Plum Print visual indicator of research metrics
PlumX Metrics
  • Citations
    • Citation Indexes: 5
  • Usage
    • Downloads: 165
    • Abstract Views: 3
see details

Included in

Mathematics Commons

Share

COinS