Pewsey, Authur and Jones, M. C.
Discrimination between the von Mises and wrapped normal distributions: just how big does the sample size have to be?
Important similarities and differences are known to exist between the von Mises and wrapped normal distributions, two of the principal models for circular data. In this paper, we consider likelihood-based approaches to determining the sample size required in order to reliably discriminate between the two models. We make use of three new misclassification probability-based criteria to establish lower and upper bounds for the sample size.
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