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

Abstract

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 through empirical interpretation.

Keywords:

• Auxiliary information
• Bias
• Chain-type
• Difference to difference
• Mean square error
• Optimum replacement policy
• Regression to regression
• Successive sampling
• Variance

Mathematics Subject Classification:

• 62D05

Acknowledgments

Authors are grateful to the referees for their valuable and inspiring suggestions. Authors are also obliged to the Indian School of Mines University for providing the financial assistance to carry out the present work.