Bayesian inference for rare errors in populations with unequal unit sizes |
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Authors: | David J Laws & Anthony O'Hagan |
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Institution: | University of Sheffield, UK |
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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. |
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Keywords: | Auditing Bayesian inference Dirichlet process Nonparametric modelling Rare errors Simulation |
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