Fisher information for generalized Rayleigh distribution in ranked set sampling design with application to parameter estimation
Bing-liang Shen, Shuo Wang, Wang-xue Chen, Meng Chen
Source record
Source: Crossref
Published: Dec 1, 2022
DOI: 10.1007/s11766-022-4450-5
Open original source ↗Source abstract
Abstract 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.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.