Favourable Allocation Models for Symmetric Distributions in Ranked Set Sampling


12

Authors

  • Neeraj Tiwari Soban Singh Jeena University, Almora
  • Girish Chandra University of Allahabad, Prayagraj
  • Raman Nautiyal Soban Singh Jeena University, Almora

https://doi.org/10.56093/jisas.v77i01.171569

Keywords:

KPT model; Neyman’s allocation; Order statistic; Ranked set sample; Relative precision; Symmetric distribution. 2020 AMS Mathematics Subject Classification: 62D05; 62G09; 94A20

Abstract

 Kaur et al. (2000) suggested an optimal allocation model for symmetric distribution in ranked set sampling (RSS). This model is not much applicable due to its dependency upon extreme or mid order statistic only. In this paper, an attempt to make a “favourable” and near optimal allocation has been made by allocating each rank order at least once and considering the opposite behavior of Neyman allocation for symmetric distribution. The case of perfect ranking is considered. The utility of the proposed model in terms of relative precision has been shown for some symmetric distributions. Favourable model outperforms both for equal and Neyman’s allocations and quite close to the optimal model for each set size. The model will provide a practical approach in situations where RSS is likely to lead to an improvement over simple random sampling and the underlying distribution is symmetric.

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References

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Kaur, A., Patil, G.P. and Taillie, C. (1997). Unequal allocation models for ranked set sampling with skew distributions. Biometrics, 53, 123-130.

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Submitted

2025-09-08

Published

2025-09-08

Issue

Section

Articles

How to Cite

Neeraj Tiwari, Girish Chandra, & Raman Nautiyal. (2025). Favourable Allocation Models for Symmetric Distributions in Ranked Set Sampling. Journal of the Indian Society of Agricultural Statistics, 77(01), 89-94. https://doi.org/10.56093/jisas.v77i01.171569
Citation