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dc.contributor.authorHall, Peter
dc.contributor.authorLombard, Fred
dc.contributor.authorPotgieter, Cornelis J.
dc.date.accessioned2016-03-15T09:55:22Z
dc.date.available2016-03-15T09:55:22Z
dc.date.issued2013
dc.identifier.citationHall, P. et al. 2013. A new approach to function-based hypothesis testing in location-scale families. Technometrics, 55(2):215-223. [http://dx.doi.org/10.1080/00401706.2013.775902]en_US
dc.identifier.issn0040-1706
dc.identifier.issn1537-2723 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/16666
dc.identifier.urihttp://dx.doi.org/10.1080/00401706.2013.775902
dc.identifier.urihttp://www.tandfonline.com/doi/full/10.1080/00401706.2013.775902
dc.description.abstractMotivated by two applications in the mining industry, we introduce a new approach to testing the hypothesis that two-sampled distributions are simply location and scale changes of one another. The test, applicable to both paired data and two-sample data, is based on the empirical characteristic function. More conventional techniques founded on the empirical distribution function suffer from serious drawbacks when used to test for location-scale families. In the motivating applications, knowing that the distributions differ only in location and scale has significant operational and economic advantages, enabling protocols for one type of data to be applied directly to another. Supplementary material in the form of Matlab code is available onlineen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectBootstrapen_US
dc.subjectempirical characteristic functionen_US
dc.subjecttesting for differences between meanen_US
dc.subjecttesting in paired samplesen_US
dc.subjecttests based on empirical distribution functionen_US
dc.subjecttwo-sample testsen_US
dc.titleA new approach to function-based hypothesis testing in location-scale familiesen_US
dc.typeArticleen_US
dc.contributor.researchID12950149 - Lombard, Frederick


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