An almost unbiased estimator for population mean using known value of population parameter(s)

TL;DR

This paper introduces an almost unbiased estimator for the population mean that leverages known auxiliary population parameters, aiming to improve estimation accuracy under simple random sampling without replacement.

Contribution

It proposes a new class of estimators incorporating known population parameters, extending existing estimators and deriving their bias and MSE expressions.

Findings

Derived expressions for bias and MSE of the proposed estimator

Numerical illustrations demonstrate improved estimation performance

Includes existing estimators as special cases

Abstract

In this paper we have proposed an almost unbiased estimator using known value of some population parameter(s) with known population proportion of an auxiliary variable. A class of estimators is defined which includes [1], [2] and [3] estimators. Under simple random sampling without replacement (SRSWOR) scheme the expressions for bias and mean square error (MSE) are derived. Numerical illustrations are given in support of the present study. Key words: Auxiliary information, proportion, bias, mean square error, unbiased estimator.