Show simple item record

dc.contributor.authorLombard, F.
dc.contributor.authorPotgieter, C. J.
dc.date.accessioned2016-02-25T12:30:49Z
dc.date.available2016-02-25T12:30:49Z
dc.date.issued2012-04
dc.identifier.citationLombard F, Potgieter CJ (2012) A multivariate rank test for comparing mass size distributions. Journal of Applied Statistics 39: 851–865. Available: http://dx.doi.org/10.1080/02664763.2011.623155.
dc.identifier.issn0266-4763
dc.identifier.issn1360-0532
dc.identifier.doi10.1080/02664763.2011.623155
dc.identifier.urihttp://hdl.handle.net/10754/597329
dc.description.abstractParticle size analyses of a raw material are commonplace in the mineral processing industry. Knowledge of particle size distributions is crucial in planning milling operations to enable an optimum degree of liberation of valuable mineral phases, to minimize plant losses due to an excess of oversize or undersize material or to attain a size distribution that fits a contractual specification. The problem addressed in the present paper is how to test the equality of two or more underlying size distributions. A distinguishing feature of these size distributions is that they are not based on counts of individual particles. Rather, they are mass size distributions giving the fractions of the total mass of a sampled material lying in each of a number of size intervals. As such, the data are compositional in nature, using the terminology of Aitchison [1] that is, multivariate vectors the components of which add to 100%. In the literature, various versions of Hotelling's T 2 have been used to compare matched pairs of such compositional data. In this paper, we propose a robust test procedure based on ranks as a competitor to Hotelling's T 2. In contrast to the latter statistic, the power of the rank test is not unduly affected by the presence of outliers or of zeros among the data. © 2012 Copyright Taylor and Francis Group, LLC.
dc.description.sponsorshipThe first author's work was supported by the National Research Foundation of South Africa. The second author's work was supported byAward No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). The authors thank the two referees for valuable comments that led to a much improved exposition of the work.
dc.publisherInforma UK Limited
dc.subjectbias testing
dc.subjectmass size distributions
dc.subjectmultivariate rank statistic
dc.titleA multivariate rank test for comparing mass size distributions
dc.typeArticle
dc.identifier.journalJournal of Applied Statistics
dc.contributor.institutionNorth-West University, Potchefstroom, South Africa
dc.contributor.institutionTexas A and M University, College Station, United States
dc.contributor.institutionUniversity of Johannesburg, Johannesburg, South Africa
kaust.grant.numberKUS-C1-016-04


This item appears in the following Collection(s)

Show simple item record