Fisher information for generalized Rayleigh distribution in ranked set sampling design with application to parameter estimation

In the current paper, we considered the Fisher information matrix from the generalized Rayleigh distribution (GR) distribution in ranked set sampling (RSS). The numerical results show that the ranked set sample carries more information about λ and α than a simple random sample of equivalent size. In...

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Bibliographic Details
Published in:Applied Mathematics-A Journal of Chinese Universities 2022-12, Vol.37 (4), p.615-630
Main Authors: Shen, Bing-liang, Wang, Shuo, Chen, Wang-xue, Chen, Meng
Format: Article
Language:English
Subjects:
Applications of Mathematics
Design parameters
Fisher information
Mathematics
Mathematics and Statistics
Parameter estimation
Random sampling
Rayleigh distribution
Sampling designs
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Summary:In the current paper, we considered the Fisher information matrix from the generalized Rayleigh distribution (GR) distribution in ranked set sampling (RSS). The numerical results show that the ranked set sample carries more information about λ and α than a simple random sample of equivalent size. In order to give more insight into the performance of RSS 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 λ and α from GR distribution in SRS and RSS are studied. The numerical results show that the modified unbiased estimator and the modified BLUE of λ and α in RSS are significantly more efficient than the ones in SRS.
ISSN:1005-1031
1993-0445
DOI:10.1007/s11766-022-4450-5