Sequential Hypothesis Testing Techniques for Pest Count Models With Nuisance Parameters

Sequential hypothesis testing in pest management applications are usually carried out using Wald's procedure or Iwao's procedure. Both of these procedures are applicable for one-parameter pest count models. The current practice for handling nuisance parameters when using the Wald procedure is to assume they are equal to specified values based on historical experience, and in the case of Iwao's procedure to assume a known mean-variance relationship such as Taylor's power law. In this article, we discuss the weaknesses of these practices, and advocate the use of Bartlett's sequential procedure as a better way to handle nuisance parameters. We also show how Bartlett's procedure can be implemented within three-hypothesis testing scenarios, where differentiation between three levels of infestation is desired.