Efficient class of ratio cum median estimators for estimating the population median

In estimation theory, the use of auxiliary information significantly improves precision while estimating population parameters. In this paper, an efficient class of ratio cum median estimators of the population median is suggested using simple random sampling without replacement. The expressions for...

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Bibliographic Details
Published in:PloS one 2023-02, Vol.18 (2), p.e0274690-e0274690
Main Authors: Subzar, Mir, Lone, Showkat Ahmad, Ekpenyong, Emmanuel J, Salam, Abdul, Aslam, Muhammad, Raja, T A, Almutlak, Salmeh A
Format: Article
Language:English
Subjects:
Approximation
Asymptotic properties
Bias
Biology and Life Sciences
Data analysis
Data mining
Data processing
Decision analysis
Estimation
Estimators
Evaluation
Mean square errors
Normal distribution
Physical Sciences
Population statistics
Random sampling
Research and Analysis Methods
Statistical sampling
Variables
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Summary:In estimation theory, the use of auxiliary information significantly improves precision while estimating population parameters. In this paper, an efficient class of ratio cum median estimators of the population median is suggested using simple random sampling without replacement. The expressions for bias and mean square error of the proposed class are derived theoretically. The condition for the asymptotic optimum estimator is obtained with its bias and mean square error expressions. Under certain realistic conditions, the asymptotic optimum estimator is more proficient, based on analytical and numerical comparisons with some existing estimators that are members of the suggested class of estimators. The superiority of the proposed ratio cum median estimators is shown through real data applications. Such a new proposed estimator will be useful in the future for data analysis and making decisions.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0274690