{"data":{"id":"10.6084/m9.figshare.c.2170502","type":"dois","attributes":{"doi":"10.6084/m9.figshare.c.2170502","prefix":"10.6084","suffix":"m9.figshare.c.2170502","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Yihuan Xu","affiliation":[],"nameIdentifiers":[]},{"name":"Iglewicz, Boris","nameType":"Personal","givenName":"Boris","familyName":"Iglewicz","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"False Discovery Versus Familywise Error Rate Approaches to Outlier Detection"}],"publisher":"Figshare","container":{},"publicationYear":2015,"subjects":[{"subject":"Space Science"},{"subject":"Genetics"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Pharmacology"},{"subject":"69999 Biological Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"80699 Information Systems not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"19999 Mathematical Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mathematics","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2015-12-23","dateType":"Created"},{"date":"2016-06-02","dateType":"Updated"},{"date":"2015","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Collection","resourceType":"Collection","resourceTypeGeneral":"Collection"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/19466315.2015.1119720","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"CC-BY","rightsUri":"http://creativecommons.org/licenses/by/3.0/us"}],"descriptions":[{"description":"Outliers, in general, are observations that deviate sufficiently from a base distribution. This study deals with outlier detection approaches for large samples from continuous univariate distributions. Investigated are the properties of a practical newer outlier detection approach based on use of a false discovery rate (FDR) method in conjunction with a robustly estimated Tukey g-and-h base distribution. Compared are the properties of a boxplot type outlier detection approach that controls the familywise error rate (FWER) with a newer FDR approach. These options are compared in terms of error rates and effects of moving the outliers gradually further from base distribution center while using 5% and 1% FDR or FWERs. Two microarray datasets are used as examples where the assumed null distributions do not fit the data well. In such cases, the proposed estimated Tukey g-and-h null distribution approach leads to superior outlier detection performance. Supplementary materials for this article are available online.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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