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General weighted extropy of minimum and maximum ranked set sampling with unequal samples

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  • Santosh Kumar Chaudhary
  • Nitin Gupta

Abstract

In industrial, environmental, and ecological investigations, ranked set sampling is a sample method that enables the experimenter to use the whole range of population values. The ranked set sampling process can be modified in two extremely helpful ways: maximum ranked set sampling with unequal samples and minimum ranked set sampling with unequal samples. They permit an increase in set size without too many ranking errors being introduced. In this article, we are defining general weighted extropy (GWJ) of minimum and maximum ranked set samples when samples are of unequal size (minRSSU and maxRSSU, respectively). Stochastic comparison and monotone properties have been studied under different situations. Additionally, we compare the extropy of these two sampling data with that of ranked set sampling data and simple random sampling data. Bounds of GWJ of minRSSU and maxRSSU have been obtained. Finally, we investigate the weighted discrimination information between simple random sampling, ranked set sampling, and minimum and maximum ranked set sampling with unequal sample sizes. Some results for equality of GWJ of minRSSU and maxRSSU under symmetric assumption are also obtained.

Suggested Citation

  • Santosh Kumar Chaudhary & Nitin Gupta, 2025. "General weighted extropy of minimum and maximum ranked set sampling with unequal samples," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 54(11), pages 3174-3199, June.
  • Handle: RePEc:taf:lstaxx:v:54:y:2025:i:11:p:3174-3199
    DOI: 10.1080/03610926.2024.2386420
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