Analysis of Exponential Product type Estimators with Embedded Imputation Techniques on Successive Occasions
Fields like agriculture, biological sciences, environmental sciences and sociological sciences comprise several real life situations which need to
be observed on various occasions so as to understand the dynamics of population over the study period. Also, these field contain chances for the
availability of missing observations due to sensitivity, experimental and instrumental errors or human errors. Thus, present article explores the
estimation of population mean using product type exponential estimator in presence and absence of non-response using auxiliary information
(negatively correlated to study variable) in two occasion rotation sampling for such applied fields. Detailed behaviour of the proposed estimators
have been discussed for both the situations and new imputation techniques have been suggested to negotiate with missing data problem. Optimum replacement strategies are discussed. The proposed product type exponential estimators are compared with well-known estimators with the help of numerical illustration which are followed by suitable recommendations.
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