Generalized Multi-Phase Multivariate Ratio Estimators for Partial Information Case Using Multi-Auxiliary Vatiables (original) (raw)

Generalized Multi-Phase Multivariate Ratio Estimators for

In this paper we propose generalized multi-phase multivariate ratio estimators in the presence of multiauxiliary variables for estimating population mean vector of variables of interest. Some special cases have been deduced from the suggested estimator in the form of remarks. The expressions for mean square errors of proposed estimators have also been derived. The suggested estimators are theoretically compared and an empirical study has also been conducted.

GENERALIZED MULTIVARIATE RATIO ESTIMATORS USING MULTIAUXILIARY

In this paper we propose a number of generalized multivariate ratio estimators for two-phase and multi-phase sampling in the presence of multi-auxiliary variables for estimating population mean for a single variable and a vector of variables of interest(s). The expressions for mean square errors are also derived. The suggested estimators are theoretically compared and an empirical study has also been conducted.

GENERALIZED REGRESSION ESTIMATORS UNDER TWO PHASE SAMPLING FOR PARTIAL INFORMATION CASE

Pakistan Journal of Statistics

In this paper multivariate ratio and regression estimators for estimating the population mean vector have been proposed using multi-auxiliary variables for partial information case. The expression of variance covariance matrix has been derived. Empirical study has been carried out to see the performance of proposed estimator over estimator proposed by Butt, et al. (2011).

Improved Ratio Estimators for Estimating Population Mean Using Auxiliary Information

International Journal of Scientific and Research Publications, 2020

The study presents ratios estimators for the finite population mean. The new proposed estimators are based on Subzar et al. (2018) estimators. The characteristics of the proposed estimators, i.e. bias and mean square error, were derived up to the first approximation by the Taylor series expansion, and the conditions for its effectiveness were established relative to some existing estimators. The effectiveness of the proposed estimators shows a significant improvement over the estimators considered in the study. The results of the empirical study show that the proposed estimators are more effective than existing estimators based on measurements of the comparison criteria.

GENERALIZED RATIO ESTIMATORS IN TWO-PHASE SAMPLING WITH TWO AUXILIARY VARIABLES

IASET Publications, 2022

This paper considers estimation of a finite population mean under two-phase sampling procedure involving two auxiliary variables with the assumption that population mean of the first (main) auxiliary variable is unknown whereas population mean of the second (additional) auxiliary variable is known accurately. This issue has been addressed by bringing out two generalized ratio-type estimators constituting two separate families/classes of estimators of course not necessarily disjoint. Some optimum properties of the proposed generalized estimators have been investigated and sufficient conditions for their superiority over the classical two-phase ratio estimator have been reported. After identifying some ratio/ratio-type estimators as specific cases of the said generalized estimators, both analytical and empirical comparisons among various estimators have been undertaken to show the effectiveness of the proposed estimation technique.