In rotation (successive) sampling, it is common practice to use the information collected on a previous occasion to improve the precision of the estimates at current occasion. The previous information may be in the form of an auxiliary character, the character under study itself, or both. In the present work, information on an auxiliary character, which is readily available on all the occasions, has been used along with the information on study character from the previous and current occasion. Consequently, chain type difference and regression estimators have been proposed for estimating the population mean at second (current) occasion in the two occasions rotation (successive) sampling. The proposed estimators have been compared with sample mean estimator when there is no matching and the optimum estimator, which is the combination of the means of the matched and unmatched portions of the sample at the second occasion. Optimum replacement policy is also discussed. Theoretical results have been justified ...

Search of Good Rotation Patterns to Improve the Precision of Estimates at Current Occasion

This article considers the problem of estimating population mean on the current (second) occasion using auxiliary information in successive sampling over two occasions. A class of estimators is defined with its properties. It is shown that the estimator envisaged by Singh (2005) is a particular member of the proposed class of estimators. The superiority of the suggested class of estimators is discussed with sample mean estimator when there is no matching, the best combined estimator given in Cochran (1977, p. 346), Sukhatme et al. (1984, p. 249), Singh's (2005) estimator, and Singh and Vishwakarma's (2007) class of estimators. Optimum replacement policy has been discussed. Numerical illustration is also given.

A General Procedure for Estimating Population Mean in Successive Sampling

Two classes of estimators for the population mean of the study character using multi-auxiliary characters with known population means in presence of nonresponse have been proposed. The expressions for bias, mean square error and conditions for attaining minimum mean square error of the proposed classes of estimators have been obtained. An empirical study has also been given in support of the problem.

On Class of Estimators for Population Mean Using Multi-Auxiliary Characters in the Presence of Non-Response

Summary - The problem of estimation of a finite population mean on the current occasion based on the samples selected over two occasions has been considered. Chaintype ratio and regression estimators have been considered to estimate the population mean at current occasion in two-occasion successive (rotation) sampling. Optimum replacement policies of proposed estimators have been discussed. Proposed estimators are empirically compared with the sample mean estimator, when there is no matching and the optimum estimator which is a linear combination of the means of the matched and unmatched portions of the sample at the current occasion.

Estimation of population mean on current occasion in two-occasion successive sampling

The problem of estimation of finite population mean on the current occasion in two-occasion successive sampling has been considered. Utilizing all the readily available information from first and second occasions, an efficient estimation procedure has been suggested. Optimum replacement policy relevant to the proposed estimation procedure has been discussed. A proposed estimator is compared with natural estimators and suitable recommendations have been made.

Effective Rotation Patterns in Successive Sampling Over Two Occasions

In practical problems, auxiliary information is often available for all units of a finite population. This paper develops sample rotation method relevant to this case. The estimators of the population means on both occasions and the formulae of their MSE (mean squared error) are given. The results are very similar to the usual ones.

Guohua Zou

Papers

Sample rotation method with auxiliary variable