Linear combination of estimators in probability proportional to sizes sampling to estimate the population mean and its robustness to optimum value

Satish Kumar Agarwal () and Mariam Al Mannai

Statistica, 2009, vol. 69, issue 1, 59-71

Abstract: In this paper we have studied the gain of efficiency and the relative bias of linear weighted estimators over conventional estimators under probability proportional to size with replacement (ppswr) sampling for a wide variety of populations. The five number summary statistics for the relative bias and the relative efficiency over conventional estimators is given for different magnitude of correlation coefficients. The computational study shows that there is a considerable gain in the efficiency of linear weighted estimators over conventional estimators. To develop the confidence of survey practitioners on linear weighted estimator, the computational study is extended to see the robustness of the linear weighted estimator by deviating the optimum value of the weight up to 50% on either side.

Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bot:rivsta:v:69:y:2009:i:1:p:59-71

Access Statistics for this article

Statistica is currently edited by Department of Statistics, University of Bologna

More articles in Statistica from Department of Statistics, University of Bologna Contact information at EDIRC.
Bibliographic data for series maintained by Giovanna Galatà ().