Fisher information in ranked set sampling from the simple linear regression model

Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this paper, we obtain explicit expressions for the Fisher information matrix in ranked set sampling (RSS) from the simple linear regression model with replicated...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 53; no. 3; pp. 1274 - 1284
Main Authors Wang, Shuo, Chen, Wangxue, Yang, Rui
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 03.03.2024
Taylor & Francis Ltd
Subjects
Fisher information
Fisher information matrix
Mathematical analysis
Random sampling
Ranked set sampling
Regression models
secondary
Simple linear regression model
Statistical analysis
Statistical inference
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Summary:Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this paper, we obtain explicit expressions for the Fisher information matrix in ranked set sampling (RSS) from the simple linear regression model with replicated observations. It has been shown to be the sum of two matrices, one of which is the Fisher information matrix based on simple random sampling (SRS). The numerical results show that RSS provides more information than SRS when the same sample size is used.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2022.2044053