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

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.

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Publication Details

Journal
Communication in Statistics- Theory and Methods
Published
2024-08-19
DOI
https://doi.org/10.1080/03610926.2024.2386420
Citations
1
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.71

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article

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

Nitin Gupta, Santosh Kumar Chaudhary
1 citations
Communication in Statistics- Theory and Methods
Statistical Distribution Estimation and Applications
0.71
article

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

Nitin Gupta, Santosh Kumar Chaudhary
article en
1 citations

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.

Communication in Statistics- Theory and MethodsVol. 54(11)
Birla Institute of Technology, Mesra (IN), Indian Institute of Technology Kharagpur (IN)
Council of Scientific and Industrial Research, India
Openalex Percentile: Top 27%
Statistical Distribution Estimation and Applications
0.71
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