{"data":{"id":"10.6084/m9.figshare.2064828","type":"dois","attributes":{"doi":"10.6084/m9.figshare.2064828","prefix":"10.6084","suffix":"m9.figshare.2064828","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Weizhen Wang","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Exact Optimal Confidence Intervals for Hypergeometric Parameters"}],"publisher":"Taylor \u0026 Francis","container":{},"publicationYear":2016,"subjects":[{"subject":"Medicine"},{"subject":"Microbiology"},{"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":"Ecology"},{"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)"},{"subject":"Cancer"},{"subject":"110309 Infectious Diseases","subjectScheme":"FOR"},{"subject":"FOS: Health sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Health sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Computational Biology"}],"contributors":[],"dates":[{"date":"2016-01-18","dateType":"Created"},{"date":"2018-08-31","dateType":"Updated"},{"date":"2016","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/01621459.2014.966191","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["10989 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"For a hypergeometric distribution, denoted by Hyper(M,N,n), where \u003ci\u003eN\u003c/i\u003e is the population size, \u003ci\u003eM\u003c/i\u003e is the number of population units with some attribute, and \u003ci\u003en\u003c/i\u003e is the given sample size, there are two parametric cases: (i) \u003ci\u003eN\u003c/i\u003e is unknown and \u003ci\u003eM\u003c/i\u003e is given; (ii) \u003ci\u003eM\u003c/i\u003e is unknown and \u003ci\u003eN\u003c/i\u003e is given. For each case, we first show that the minimum coverage probability of commonly used approximate intervals is much smaller than the nominal level for any \u003ci\u003en\u003c/i\u003e, then we provide exact smallest lower and upper one-sided confidence intervals and an exact admissible two-sided confidence interval, a complete set of solutions, for each parameter. Supplementary materials for this article are available online.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://tandf.figshare.com/articles/dataset/Exact_Optimal_Confidence_Intervals_for_Hypergeometric_Parameters/2064828/1","contentUrl":null,"metadataVersion":5,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"viewsOverTime":[],"downloadCount":0,"downloadsOverTime":[],"referenceCount":0,"citationCount":0,"citationsOverTime":[],"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2016-01-18T13:43:29.000Z","registered":"2016-01-18T13:43:30.000Z","published":"2016","updated":"2020-09-04T13:24:59.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.2064828","type":"media"}},"references":{"data":[]},"citations":{"data":[]},"parts":{"data":[]},"partOf":{"data":[]},"versions":{"data":[]},"versionOf":{"data":[]}}}}