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Estimation from binomial data with classifiers of known and unknown imperfections
Author(s) -
Johnson Norman L.,
Kotz Samuel
Publication year - 1988
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/1520-6750(198802)35:1<147::aid-nav3220350113>3.0.co;2-c
Subject(s) - estimator , statistics , mathematics , binomial (polynomial) , moment (physics) , maximum likelihood , standard error , population , physics , classical mechanics , demography , sociology
Observations from inspection by a “test” method and a standard method are combined to provide estimators of population proportion, and of probabilities of misclassification for the test method. Results of Hochberg and Tenenbein [3] and of Albers and Veldman [1] are extended to the case where the standard method is not perfect, but its misclassification probabilities have known values. Both moment and maximum‐likelihood estimators are considered and some asymptotic properties of the resulting estimators are compared.