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Maximum likelihood estimators of the parameters of the log-logistic distribution

Xiaofang He, Wangxue Chen (chenwangxue2015@163.com) and Wenshu Qian
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Xiaofang He: Jishou University
Wangxue Chen: Jishou University
Wenshu Qian: Jishou University

Statistical Papers, 2020, vol. 61, issue 5, No 5, 1875-1892

Abstract: Abstract In this article, maximum likelihood estimator(s) (MLE(s)) of the scale and shape parameters $$\alpha $$ α and $$\beta $$ β from log-logistic distribution will be respectively considered in cases when one parameter is known and when both are unknown under simple random sampling (SRS) and ranked set sampling (RSS). In addition, the MLE of one parameter, when another parameter is known using a RSS version based on the order statistic that maximizes the Fisher information for a fixed set size, will be considered. These MLEs will be compared in terms of asymptotic efficiencies. These MLEs based on RSS can be real competitors against those based on SRS. All efficiencies of these MLEs are simulated under imperfect ranking.

Keywords: Ranked set sample; Maximum likelihood estimator; Fisher information number (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s00362-018-1011-3

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