An Effective Estimation Strategy for Population Mean over Successive Sampling of h Occasion

Two-occasion sampling might only provide a snapshot of the phenomenon under investigation. Extending to h occasions allows researchers to capture long-term trends, patterns, and changes that may emerge over time. In h-occasion successive sampling, the effective estimation of population mean is an important factor for agriculture, socioeconomic, pandemics surveys when reliable estimates are required at the h-th occasion (recent-occasion). A difference-type model of an estimator is suggested for the estimation which is escorted with the information on two auxiliary variables. The optimal estimator is the combination of the matched and unmatched sample units in the h-occasion successive sampling. Empirical studies with the competent natural mean estimator and difference type estimator based on bias and mean square errors have been demonstrated in the estimator's efficiency context. A data analysis has been conducted for the applicability to the suggested model. The approach of this work provides valuable insights into long-term trends, developmental trajectories, causal relationships, and the dynamic nature of the real-world problems.