Abstract
In the current paper, we considered the Fisher information matrix from generalized Rayleigh distribution (GR) distribution in moving extremes ranked set sampling (MERSS). The numerical results show that the ranked set sample carry more information about \(\lambda\) and \(\alpha\) than a simple random sample of equivalent size. In order to give more insight into the performance of MERSS with respect to (w.r.t.) simple random sampling (SRS), a modified unbiased estimator and a modified best linear unbiased estimator (BLUE) of scale and shape \(\lambda\) and \(\alpha\) from GR distribution in SRS and MERSS are studied. The numerical results show that the modified unbiased estimator and the modified BLUE of \(\lambda\) and \(\alpha\) in MERSS are significantly more efficient than the ones in SRS.
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On behalf of all authors, the corresponding author states that there is no conflict of interest. The authors are thankful to the editor in chief, an associate editor and reviewers for their valuable comments and suggestions to improve the paper.
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This research was supported by National Science Foundation of China (Grant Nos. 12261036 and 11901236), Scientific Research Fund of Hunan Provincial Education Department (Grant No. 21A0328), Provincial Natural Science Foundation of Hunan (Grant No. 2022JJ30469) and Young Core Teacher Foundation of Hunan Province (Grant No. [2020]43).
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Appendix
Appendix
The log-likelihood function for a
Proof of Theorem 1
single observation
where \(d_0\) is a value which is free of \(\alpha\) and \(\lambda\). In order to compute the Fisher information matrix in MERSS, the first derivative and the second derivative of \(L_{MERSS}^*\) are respectively computed as
and
Then under the assumed regularity conditions of Theorem 1
and
The Theorem is proved by combining \(I_{11,~MERSS}\), \(I_{12,~MERSS}\) with \(I_{22,~MERSS}\).
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Shen, B., Chen, W., Zhou, Y. et al. Sampling Information for Generalized Rayleigh Distribution with Application to Parameter Estimation. Iran J Sci 47, 515–529 (2023). https://doi.org/10.1007/s40995-023-01428-4
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DOI: https://doi.org/10.1007/s40995-023-01428-4