An optimal approach for hypothesis testing in the presence of incomplete data

DOI10.1007/s10463-010-0270-0zbMath1230.62019OpenAlexW1997713064MaRDI QIDQ652615

Albert Vexler, Sergey Tarima

Publication date: 14 December 2011

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-010-0270-0

zbMATH Keywords

likelihood ratiomaximum likelihoodmissing datamost powerful testparametric hypothesis testing

Mathematics Subject Classification ID

Related Items (1)

An empirical likelihood ratio based goodness-of-fit test for inverse Gaussian distributions

Uses Software

• bootstrap

Cites Work

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• Optimality and almost optimality of mixture stopping rules
• On the average run length to false alarm in surveillance problems which possess an invariance structure
• Asymptotically uniformly most powerful tests in parametric and semiparametric models
• Testing Against a High Dimensional Alternative
• Surveillance of a Simple Linear Regression
• Hypothesis Testing: From p Values to Bayes Factors
• Integrated Risk of Asymptotically Bayes Sequential Tests

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