A Pioneering Approach to Population Mean Estimation Leveraging Ranked Set Successive Sampling
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Authors
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Kumari Priyanka
Shivaji College (University of Delhi), New Delhi
Keywords:
Ranked Set Successive Sampling; Auxiliary variable; Mean squared error; Relative efficiency.Abstract
Ranked set sampling has been observed to be an efficient sampling method that has gained popularity in recent years. In the present work, the
concept of ranked set sampling has been extended to successive sampling, which results in a novel sampling scheme called Ranked Set Successive
Sampling (RSSS). The theoretical foundation of RSSS has been discussed and estimation methodologies has been modified to be applicable in
RSSS environment for the estimation of population mean. RSSS has been considered for two successive occasions, and the estimators are proposed
for estimating the population mean at current (second) occasion in two-occasion RSSS. The performance of the proposed estimators are examined
through simulation-based evaluation including the real data applications as well as simulated populations. The simulation results shows that the
concept of RSSS is practically feasible. The comparative analysis reveals that the proposed estimators under RSSS exhibit improved efficiency over
the available similar successive sampling estimators, which may be applicable in various real-life situations.
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