Bayesian analysis of a quarantine inspection model

David P. M. Scollnik

Journal of Applied Statistics, 2018, vol. 45, issue 8, 1484-1496

Abstract: In this paper, we propose a quarantine inspection model and examine its analysis from a Bayesian point of view. This model is a generalization of the one appearing in Decrouez and Robinson [Aust. N. Z. J. Stat., 54 (2012), pp. 281–299]. The context has to do with items approaching a border, some of which are randomly selected and inspected for contamination. A random sample of the items that pass this first inspection is submitted to a second inspection that is assumed to detect all contamination. Inference is sought with respect to the model parameters and also especially the proportion of items that pass through the border that are still contaminated. A hierarchical quarantine inspection model is also introduced and discussed. Three illustrative examples are given.

Date: 2018
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DOI: 10.1080/02664763.2017.1380785

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