Hartley-Ross Type Unbiased Estimators of Population Mean Using Two Auxiliary Variables

A class of Hartley-Ross type Unbiased estimators for Population Mean using Ranked Set Sampling

In this paper, we propose a class of Hartley-Ross type unbiased estimators for estimating the finite population mean of the study variable under ranked set sampling (RSS), when population mean of the auxiliary variable is known. The variances of the proposed class of unbiased estimators are obtained to first degree of approximation. Both theoretically and numerically, the proposed estimators ar...

A Class of Ratio Estimators of a Finite Population Mean Using Two Auxiliary Variables

In sample surveys, it is usual to increase the efficiency of the estimators by the use of the auxiliary information. We propose a class of ratio estimators of a finite population mean using two auxiliary variables and obtain mean square error (MSE) equations for the class of proposed estimators. We find theoretical conditions that make proposed family estimators more efficient than the traditio...

A Family of Estimators of Population Mean Using Information on Two Auxiliary Attribute

Submitted: May 23, 2013; Accepted: Jul 3, 2013; Published: Jul 19, 2013 Abstract: This paper deals with the problem of estimating the finite population mean when some information on two auxiliary attributes are available. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The study is also extended to two-phase sampling. The re...

Some Improved Estimators of Population Mean Using Information on Two Auxiliary Attributes

Improvement in Estimating Population Mean using Two Auxiliary Variables in Two-Phase Sampling

This study proposes improved chain-ratio type estimator for estimating population mean using some known values of population parameter(s) of the second auxiliary character. The proposed estimators have been compared with two-phase ratio estimator and some other chain ratio type estimators. The performances of the proposed estimators have been supported with a numerical illustration.