{"data":{"id":"10.6084/m9.figshare.c.2175198","type":"dois","attributes":{"doi":"10.6084/m9.figshare.c.2175198","prefix":"10.6084","suffix":"m9.figshare.c.2175198","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Weizhen Wang","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Exact Optimal Confidence Intervals for Hypergeometric Parameters"}],"publisher":"Figshare","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":"Infectious Diseases"},{"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":"2016-04-29","dateType":"Updated"},{"date":"2016","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Collection","resourceType":"Collection","resourceTypeGeneral":"Collection"},"relatedIdentifiers":[],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"CC-BY","rightsUri":"http://creativecommons.org/licenses/by/3.0/us"}],"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":"PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0iVVRGLTgiPz4KPHJlc291cmNlIHhtbG5zOnhzaT0iaHR0cDovL3d3dy53My5vcmcvMjAwMS9YTUxTY2hlbWEtaW5zdGFuY2UiIHhtbG5zPSJodHRwOi8vZGF0YWNpdGUub3JnL3NjaGVtYS9rZXJuZWwtNCIgeHNpOnNjaGVtYUxvY2F0aW9uPSJodHRwOi8vZGF0YWNpdGUub3JnL3NjaGVtYS9rZXJuZWwtNCBodHRwOi8vc2NoZW1hLmRhdGFjaXRlLm9yZy9tZXRhL2tlcm5lbC00L21ldGFkYXRhLnhzZCI+CiAgPGlkZW50aWZpZXIgaWRlbnRpZmllclR5cGU9IkRPSSI+MTAuNjA4NC9NOS5GSUdTSEFSRS5DLjIxNzUxOTg8L2lkZW50aWZpZXI+CiAgPGNyZWF0b3JzPgogICAgPGNyZWF0b3I+CiAgICAgIDxjcmVhdG9yTmFtZT5XZWl6aGVuIFdhbmc8L2NyZWF0b3JOYW1lPgogICAgPC9jcmVhdG9yPgogIDwvY3JlYXRvcnM+CiAgPHRpdGxlcz4KICAgIDx0aXRsZT5FeGFjdCBPcHRpbWFsIENvbmZpZGVuY2UgSW50ZXJ2YWxzIGZvciBIeXBlcmdlb21ldHJpYyBQYXJhbWV0ZXJzPC90aXRsZT4KICA8L3RpdGxlcz4KICA8cHVibGlzaGVyPkZpZ3NoYXJlPC9wdWJsaXNoZXI+CiAgPHB1YmxpY2F0aW9uWWVhcj4yMDE2PC9wdWJsaWNhdGlvblllYXI+CiAgPHJlc291cmNlVHlwZSByZXNvdXJjZVR5cGVHZW5lcmFsPSJDb2xsZWN0aW9uIj5Db2xsZWN0aW9uPC9yZXNvdXJjZVR5cGU+CiAgPHN1YmplY3RzPgogICAgPHN1YmplY3Q+TWVkaWNpbmU8L3N1YmplY3Q+CiAgICA8c3ViamVjdD5NaWNyb2Jpb2xvZ3k8L3N1YmplY3Q+CiAgICA8c3ViamVjdCBzdWJqZWN0U2NoZW1lPSJGaWVsZHMgb2YgU2NpZW5jZSBhbmQgVGVjaG5vbG9neSAoRk9TKSIgc2NoZW1lVVJJPSJodHRwOi8vd3d3Lm9lY2Qub3JnL3NjaWVuY2UvaW5uby8zODIzNTE0Ny5wZGYiPkZPUzogQmlvbG9naWNhbCBzY2llbmNlczwvc3ViamVjdD4KICAgIDxzdWJqZWN0IHN1YmplY3RTY2hlbWU9IkZpZWxkcyBvZiBTY2llbmNlIGFuZCBUZWNobm9sb2d5IChGT1MpIj5GT1M6IEJpb2xvZ2ljYWwgc2NpZW5jZXM8L3N1YmplY3Q+CiAgICA8c3ViamVjdD5FY29sb2d5PC9zdWJqZWN0PgogICAgPHN1YmplY3Qgc3ViamVjdFNjaGVtZT0iRk9SIj4xOTk5OSBNYXRoZW1hdGljYWwgU2NpZW5jZXMgbm90IGVsc2V3aGVyZSBjbGFzc2lmaWVkPC9zdWJqZWN0PgogICAgPHN1YmplY3Qgc3ViamVjdFNjaGVtZT0iRmllbGRzIG9mIFNjaWVuY2UgYW5kIFRlY2hub2xvZ3kgKEZPUykiIHNjaGVtZVVSST0iaHR0cDovL3d3dy5vZWNkLm9yZy9zY2llbmNlL2lubm8vMzgyMzUxNDcucGRmIj5GT1M6IE1hdGhlbWF0aWNzPC9zdWJqZWN0PgogICAgPHN1YmplY3Qgc3ViamVjdFNjaGVtZT0iRmllbGRzIG9mIFNjaWVuY2UgYW5kIFRlY2hub2xvZ3kgKEZPUykiPkZPUzogTWF0aGVtYXRpY3M8L3N1YmplY3Q+CiAgICA8c3ViamVjdD5DYW5jZXI8L3N1YmplY3Q+CiAgICA8c3ViamVjdD5JbmZlY3Rpb3VzIERpc2Vhc2VzPC9zdWJqZWN0PgogICAgPHN1YmplY3Qgc3ViamVjdFNjaGVtZT0iRmllbGRzIG9mIFNjaWVuY2UgYW5kIFRlY2hub2xvZ3kgKEZPUykiIHNjaGVtZVVSST0iaHR0cDovL3d3dy5vZWNkLm9yZy9zY2llbmNlL2lubm8vMzgyMzUxNDcucGRmIj5GT1M6IEhlYWx0aCBzY2llbmNlczwvc3ViamVjdD4KICAgIDxzdWJqZWN0IHN1YmplY3RTY2hlbWU9IkZpZWxkcyBvZiBTY2llbmNlIGFuZCBUZWNobm9sb2d5IChGT1MpIj5GT1M6IEhlYWx0aCBzY2llbmNlczwvc3ViamVjdD4KICAgIDxzdWJqZWN0PkNvbXB1dGF0aW9uYWwgQmlvbG9neTwvc3ViamVjdD4KICA8L3N1YmplY3RzPgogIDxkYXRlcz4KICAgIDxkYXRlIGRhdGVUeXBlPSJDcmVhdGVkIj4yMDE2LTAxLTE4PC9kYXRlPgogICAgPGRhdGUgZGF0ZVR5cGU9IlVwZGF0ZWQiPjIwMTYtMDQtMjk8L2RhdGU+CiAgICA8ZGF0ZSBkYXRlVHlwZT0iSXNzdWVkIj4yMDE2PC9kYXRlPgogIDwvZGF0ZXM+CiAgPHNpemVzLz4KICA8Zm9ybWF0cy8+CiAgPHZlcnNpb24vPgogIDxyaWdodHNMaXN0PgogICAgPHJpZ2h0cyByaWdodHNVUkk9Imh0dHA6Ly9jcmVhdGl2ZWNvbW1vbnMub3JnL2xpY2Vuc2VzL2J5LzMuMC91cyI+Q0MtQlk8L3JpZ2h0cz4KICA8L3JpZ2h0c0xpc3Q+CiAgPGRlc2NyaXB0aW9ucz4KICAgIDxkZXNjcmlwdGlvbiBkZXNjcmlwdGlvblR5cGU9IkFic3RyYWN0Ij5Gb3IgYSBoeXBlcmdlb21ldHJpYyBkaXN0cmlidXRpb24sIGRlbm90ZWQgYnkgSHlwZXIoTSxOLG4pLCB3aGVyZSAmbHQ7aSZndDtOJmx0Oy9pJmd0OyBpcyB0aGUgcG9wdWxhdGlvbiBzaXplLCAmbHQ7aSZndDtNJmx0Oy9pJmd0OyBpcyB0aGUgbnVtYmVyIG9mIHBvcHVsYXRpb24gdW5pdHMgd2l0aCBzb21lIGF0dHJpYnV0ZSwgYW5kICZsdDtpJmd0O24mbHQ7L2kmZ3Q7IGlzIHRoZSBnaXZlbiBzYW1wbGUgc2l6ZSwgdGhlcmUgYXJlIHR3byBwYXJhbWV0cmljIGNhc2VzOiAoaSkgJmx0O2kmZ3Q7TiZsdDsvaSZndDsgaXMgdW5rbm93biBhbmQgJmx0O2kmZ3Q7TSZsdDsvaSZndDsgaXMgZ2l2ZW47IChpaSkgJmx0O2kmZ3Q7TSZsdDsvaSZndDsgaXMgdW5rbm93biBhbmQgJmx0O2kmZ3Q7TiZsdDsvaSZndDsgaXMgZ2l2ZW4uIEZvciBlYWNoIGNhc2UsIHdlIGZpcnN0IHNob3cgdGhhdCB0aGUgbWluaW11bSBjb3ZlcmFnZSBwcm9iYWJpbGl0eSBvZiBjb21tb25seSB1c2VkIGFwcHJveGltYXRlIGludGVydmFscyBpcyBtdWNoIHNtYWxsZXIgdGhhbiB0aGUgbm9taW5hbCBsZXZlbCBmb3IgYW55ICZsdDtpJmd0O24mbHQ7L2kmZ3Q7LCB0aGVuIHdlIHByb3ZpZGUgZXhhY3Qgc21hbGxlc3QgbG93ZXIgYW5kIHVwcGVyIG9uZS1zaWRlZCBjb25maWRlbmNlIGludGVydmFscyBhbmQgYW4gZXhhY3QgYWRtaXNzaWJsZSB0d28tc2lkZWQgY29uZmlkZW5jZSBpbnRlcnZhbCwgYSBjb21wbGV0ZSBzZXQgb2Ygc29sdXRpb25zLCBmb3IgZWFjaCBwYXJhbWV0ZXIuIFN1cHBsZW1lbnRhcnkgbWF0ZXJpYWxzIGZvciB0aGlzIGFydGljbGUgYXJlIGF2YWlsYWJsZSBvbmxpbmUuPC9kZXNjcmlwdGlvbj4KICA8L2Rlc2NyaXB0aW9ucz4KPC9yZXNvdXJjZT4K","url":"https://figshare.com/collections/Exact_Optimal_Confidence_Intervals_for_Hypergeometric_Parameters/2175198","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","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":"2016-01-18T13:43:27.000Z","registered":"2016-01-18T13:43:28.000Z","published":"2016","updated":"2024-12-14T20:52:04.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.c.2175198","type":"media"}},"references":{"data":[]},"citations":{"d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