{"id":"https://openalex.org/W2002212084","doi":"https://doi.org/10.1198/004017005000000355","title":"One-Sided Approximate Prediction Intervals for at Least<i>p</i>of<i>m</i>Observations From a Gamma Population at Each of<i>r</i>Locations","display_name":"One-Sided Approximate Prediction Intervals for at Least<i>p</i>of<i>m</i>Observations From a Gamma Population at Each of<i>r</i>Locations","publication_year":2006,"publication_date":"2006-01-17","ids":{"openalex":"https://openalex.org/W2002212084","doi":"https://doi.org/10.1198/004017005000000355","mag":"2002212084"},"language":"en","primary_location":{"id":"doi:10.1198/004017005000000355","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017005000000355","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024199442","display_name":"Dulal K. Bhaumik","orcid":"https://orcid.org/0000-0002-5182-4777"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dulal Kumar Bhaumik","raw_affiliation_strings":["Center for Health Statistics, Departments of Biostatistics and Psychiatry, University of Illinois, Chicago, IL 60612","Psychiatry"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Health Statistics, Departments of Biostatistics and Psychiatry, University of Illinois, Chicago, IL 60612","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Psychiatry","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030674909","display_name":"Robert D. Gibbons","orcid":"https://orcid.org/0000-0002-6463-2280"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert David Gibbons","raw_affiliation_strings":["Center for Health Statistics, Departments of Biostatistics and Psychiatry, University of Illinois, Chicago, IL 60612","University of Illinois at Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Health Statistics, Departments of Biostatistics and Psychiatry, University of Illinois, Chicago, IL 60612","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"University of Illinois at Chicago","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":1.8307,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.85710021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"48","issue":"1","first_page":"112","last_page":"119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.7745612859725952},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.589238166809082},{"id":"https://openalex.org/keywords/gamma-distribution","display_name":"Gamma distribution","score":0.565171480178833},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5380982756614685},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5198812484741211},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.5184826254844666},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5073882937431335},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46753188967704773},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.45583418011665344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45510542392730713},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.45218461751937866},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.44770294427871704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3355066776275635},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30111053586006165},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10050597786903381},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09423750638961792}],"concepts":[{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.7745612859725952},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.589238166809082},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.565171480178833},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5380982756614685},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5198812484741211},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.5184826254844666},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5073882937431335},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46753188967704773},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.45583418011665344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45510542392730713},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.45218461751937866},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.44770294427871704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3355066776275635},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30111053586006165},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10050597786903381},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09423750638961792},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1198/004017005000000355","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017005000000355","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W656353280","https://openalex.org/W1970655212","https://openalex.org/W1977023253","https://openalex.org/W1984936791","https://openalex.org/W1991567646","https://openalex.org/W1993289772","https://openalex.org/W1995017987","https://openalex.org/W1999336195","https://openalex.org/W2000166713","https://openalex.org/W2002415910","https://openalex.org/W2008385258","https://openalex.org/W2008441678","https://openalex.org/W2015457120","https://openalex.org/W2037509330","https://openalex.org/W2052769277","https://openalex.org/W2053289371","https://openalex.org/W2064379201","https://openalex.org/W2087982347","https://openalex.org/W2125418147","https://openalex.org/W2222224277","https://openalex.org/W2331898814","https://openalex.org/W2554928058","https://openalex.org/W2801914020","https://openalex.org/W3146145917","https://openalex.org/W4234875817","https://openalex.org/W4241141159","https://openalex.org/W4244150008","https://openalex.org/W4253120075","https://openalex.org/W4256149475"],"related_works":["https://openalex.org/W2096947471","https://openalex.org/W2011903341","https://openalex.org/W1485223389","https://openalex.org/W2013882407","https://openalex.org/W1981436518","https://openalex.org/W2897428363","https://openalex.org/W2401523190","https://openalex.org/W2164993559","https://openalex.org/W2794649148","https://openalex.org/W2040597492"],"abstract_inverted_index":{"AbstractWe":[0],"develop":[1,14],"simultaneous":[2,59,137],"approximate":[3,138],"statistical":[4],"prediction":[5,17,80],"limits":[6,191],"for":[7,20,63],"a":[8,33,101,152],"gamma-distributed":[9],"random":[10],"variable.":[11],"Specifically,":[12],"we":[13],"an":[15,52,75,93,179],"upper":[16],"limit":[18],"(UPL)":[19],"p":[21,114],"of":[22,28,36,51,54,74,78,92,117,125,136,142,145,156],"m":[23,119],"future":[24],"samples":[25,86,122],"at":[26,112],"each":[27,124],"r":[29,106,127],"locations,":[30],"based":[31],"on":[32,95],"previous":[34],"sample":[35],"n":[37],"measurements.":[38],"A":[39],"typical":[40],"example":[41,180],"is":[42,56],"the":[43,49,72,79,96,109,118,126,131,143,146,165],"environmental":[44,150],"monitoring":[45,68,103,183],"problem":[46],"in":[47,71,123],"which":[48],"distribution":[50,148],"analyte":[53],"concern":[55],"typically":[57],"non-Gaussian,":[58],"determinations":[60],"are":[61,87],"required":[62],"multiple":[64],"locations":[65],"(e.g.,":[66],"ground-water":[67,102,182],"wells),":[69],"and,":[70],"event":[73],"initial":[76],"exceedance":[77],"limit,":[81],"one":[82],"or":[83],"more":[84],"verification":[85],"obtained":[88],"to":[89,149],"confirm":[90],"evidence":[91],"impact":[94],"environment.":[97],"For":[98],"example,":[99],"consider":[100],"program":[104],"with":[105,169],"wells":[107,128],"and":[108,159,167,171,178],"requirement":[110],"that":[111,175],"least":[113],"=":[115,120],"1":[116],"2":[121],"be":[129],"below":[130],"UPL.":[132],"We":[133],"provide":[134],"derivation":[135],"gamma":[139,147],"UPLs,":[140],"illustration":[141],"relevance":[144],"data,":[151],"limited":[153],"simulation":[154],"study":[155],"type":[157],"I":[158],"II":[160],"error":[161],"rates":[162],"achieved":[163],"using":[164,181],"method":[166],"comparison":[168],"normal":[170],"nonparametric":[172],"alternatives,":[173],"tables":[174],"aid":[176],"computation,":[177],"data.KEY":[184],"WORDS":[185],":":[186],"Censored":[187],"dataEnvironmental":[188],"monitoringGamma":[189],"distributionPrediction":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}