Discrimination information;
imperfect judgment ranking;
ranked set sampling;
stochastic orders;
Tsallis entropy;
NONEXTENSIVE STATISTICAL-MECHANICS;
INFORMATION PROPERTIES;
PERFECT RANKING;
EXTREME;
D O I:
10.1080/02331888.2025.2460593
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
Ranked set sampling scheme has an important role in different scientific areas. Comparison between the information contained in samples based on different sampling schemes has been widely discussed in the literature. It has been emphasized that the information contained in ranked set samples is more than that of simple random samples of the same size based on Fisher information, Shannon entropy, extropy, R & egrave;nyi and Kullback-Leibler information. According to this essay, the effect of imperfect rankings on uncertainty and information contained in samples is studied in terms of Tsallis entropy. Further, we inquire about monotonic properties under the imperfect and perfect rankings by means of stochastic orders. Tsallis entropy of simple random sampling is compared to the ranked set sampling and maximum ranked set sampling with unequal sample sizes schemes under both perfect and imperfect rankings. Finally, discrimination information of order alpha is studied between the mentioned data sets.
机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
Yu, PLH
Tam, CYC
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机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
机构:
Univ Kebangsaan Malaysia, Fac Sci & Technol, Sch Math Sci, Ukm Bangi 43600, Selangor DE, MalaysiaUniv Kebangsaan Malaysia, Fac Sci & Technol, Sch Math Sci, Ukm Bangi 43600, Selangor DE, Malaysia
机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
Yu, PLH
Tam, CYC
论文数: 0引用数: 0
h-index: 0
机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
机构:
Univ Kebangsaan Malaysia, Fac Sci & Technol, Sch Math Sci, Ukm Bangi 43600, Selangor DE, MalaysiaUniv Kebangsaan Malaysia, Fac Sci & Technol, Sch Math Sci, Ukm Bangi 43600, Selangor DE, Malaysia