Estimation of population mean in successive sampling under super-population model in presence of random non response situations

Abstract

The present work is an attempt to estimate the population mean on the current occasion in two-occasion successive (rotation) sampling in presence of random non response situations. The estimation strategy has been constructed under a super-population model design approach with the help of imputation technique. The estimators proposed on the current occasion cover the cases of occurrences random non responses on either of the occasions. Detail behaviors of the proposed class of estimators have been studied and its performance has been examined with the sample mean estimator. The results are demonstrated through empirical studies which establish the effectiveness of the proposed class of estimators. Suitable recommendations have been put forward to the survey statisticians for its practical application.

Keywords:

• Auxiliary variable
• expected variance
• linear model
• optimum replacement policy
• successive sampling
• super-population model

Mathematics Subject Classification:

• 62D05