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Estimation from binomial data with classifiers of known and unknown imperfections

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  • Norman L. Johnson
  • Samuel Kotz

Abstract

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.

Suggested Citation

  • Norman L. Johnson & Samuel Kotz, 1988. "Estimation from binomial data with classifiers of known and unknown imperfections," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(1), pages 147-156, February.
    • Handle: RePEc:wly:navres:v:35:y:1988:i:1:p:147-156
    DOI: 10.1002/1520-6750(198802)35:13.0.CO;2-C
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    Cited by:

    1. Roberto Quinino & Linda Ho & Emílio Suyama, 2013. "Alternative estimator for the parameters of a mixture of two binomial distributions," Statistical Papers, Springer, vol. 54(1), pages 47-69, February.
    2. Ricardo Saldanha Morais & Roberto da Costa Quinino & Emilio Suyama & Linda Lee Ho, 2019. "Estimators of parameters of a mixture of three multinomial distributions based on simple majority results," Statistical Papers, Springer, vol. 60(4), pages 1283-1316, August.

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