On discrimination procedure with mixtures of continuous and categorical variables

dc.contributor.authorOyeyemi, G. M.
dc.contributor.authorMbaeyi, G. C.
dc.contributor.authorSalau, I. S.
dc.contributor.authorMuse, B. O.
dc.date.accessioned2023-07-27T08:54:16Z
dc.date.available2023-07-27T08:54:16Z
dc.date.issued2016
dc.description.abstractA discrimination procedure, based on the location model is described and suggested for use in situation where the discriminating variables are mixtures of continuous and binary variables. Some procedures that have been previously employed, in a similar situation, like Fisher’s linear discriminant function and the logistic regression were compared with this method using error rate (ER). Optimal ERs for these procedures are reported using real and simulated data for the case of varying sample size and number of continuous and binary variables and were used as a measure for assessing the performance of the various procedures. The suggested procedure performed considerably better in the cases considered and never did produce a result that is poor when compared with other procedures. Hence, the suggested procedure might be considered for such situations.en_US
dc.description.sponsorshipSelf-sponsoreden_US
dc.identifier.citationJournal of Applied Statisticsen_US
dc.identifier.issn0266 - 4763
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11622
dc.language.isoenen_US
dc.publisherTaylor and Francisen_US
dc.relation.ispartofseries43(10);1864-1873
dc.subjectLocation model, Error rate, Discriminanten_US
dc.titleOn discrimination procedure with mixtures of continuous and categorical variablesen_US
dc.typeArticleen_US

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