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Bayesian inference for rare errors in populations with unequal unit sizes

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  • David J. Laws
  • Anthony O'Hagan

Abstract

We describe a Bayesian model for a scenario in which the population of errors contains many 0s and there is a known covariate. This kind of structure typically occurs in auditing, and we use auditing as the driving application of the method. Our model is based on a categorization of the error population together with a Bayesian nonparametric method of modelling errors within some of the categories. Inference is through simulation. We conclude with an example based on a data set provided by the UK's National Audit Office.

Suggested Citation

  • David J. Laws & Anthony O'Hagan, 2000. "Bayesian inference for rare errors in populations with unequal unit sizes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(4), pages 577-590.
    • Handle: RePEc:bla:jorssc:v:49:y:2000:i:4:p:577-590
    DOI: 10.1111/1467-9876.00213
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    Cited by:

    1. Raats, V.M. & Moors, J.J.A. & van der Genugten, B.B., 2004. "A Mixed Model for Double Checking Fallible Auditors," Discussion Paper 2004-82, Tilburg University, Center for Economic Research.
    2. S. K. Sahu & T. M. F. Smith, 2006. "A Bayesian method of sample size determination with practical applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 235-253, March.
    3. Raats, V.M. & Moors, J.J.A. & van der Genugten, B.B., 2004. "A Mixed Model for Double Checking Fallible Auditors," Other publications TiSEM 847311c8-d871-4942-b5e3-8, Tilburg University, School of Economics and Management.

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