The Open UniversitySkip to content
 

Discrimination between the von Mises and wrapped normal distributions: just how big does the sample size have to be?

Pewsey, Authur and Jones, M. C. (2005). Discrimination between the von Mises and wrapped normal distributions: just how big does the sample size have to be? Statistics, 39(2) pp. 81–89.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1080/02331880500031597
Google Scholar: Look up in Google Scholar

Abstract

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.

Item Type: Journal Article
Copyright Holders: 2005 Taylor & Francis
ISSN: 0233-1888
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 18230
Depositing User: Colin Smith
Date Deposited: 04 Sep 2009 09:33
Last Modified: 02 Dec 2010 20:37
URI: http://oro.open.ac.uk/id/eprint/18230
Share this page:

Actions (login may be required)

View Item
Report issue / request change

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk