{"id":"https://openalex.org/W2160478145","doi":"https://doi.org/10.1198/004017008000000091","title":"Analysis of Window-Observation Recurrence Data","display_name":"Analysis of Window-Observation Recurrence Data","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W2160478145","doi":"https://doi.org/10.1198/004017008000000091","mag":"2160478145"},"language":"en","primary_location":{"id":"doi:10.1198/004017008000000091","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017008000000091","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/A5055995551","display_name":"Jianying Zuo","orcid":null},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianying Zuo","raw_affiliation_strings":["Department of Statistics Iowa State University Ames, IA 50011","Iowa State University\u2028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics Iowa State University Ames, IA 50011","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Iowa State University\u2028","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086128963","display_name":"William Q. Meeker","orcid":"https://orcid.org/0000-0002-5366-0294"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Q. Meeker","raw_affiliation_strings":["Department of Statistics Iowa State University Ames, IA 50011","Iowa State University\u2028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics Iowa State University Ames, IA 50011","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Iowa State University\u2028","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007571830","display_name":"Huaiqing Wu","orcid":"https://orcid.org/0000-0001-7815-2459"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huaiqing Wu","raw_affiliation_strings":["Department of Statistics Iowa State University Ames, IA 50011","Iowa State University\u2028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics Iowa State University Ames, IA 50011","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Iowa State University\u2028","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I173911158"],"apc_list":null,"apc_paid":null,"fwci":0.5774,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.72531215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"50","issue":"2","first_page":"128","last_page":"143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9968000054359436,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9968000054359436,"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/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9915000200271606,"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/censoring","display_name":"Censoring (clinical trials)","score":0.7698659896850586},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.7468112707138062},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7108157277107239},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.5882716178894043},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5745805501937866},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5681036710739136},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.521697461605072},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4923590421676636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.415706604719162},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41361430287361145},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.36252477765083313},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35378676652908325},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32611948251724243}],"concepts":[{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.7698659896850586},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.7468112707138062},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7108157277107239},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.5882716178894043},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5745805501937866},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5681036710739136},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.521697461605072},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4923590421676636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.415706604719162},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41361430287361145},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36252477765083313},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35378676652908325},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32611948251724243},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1198/004017008000000091","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017008000000091","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"},{"id":"pmh:oai:lib.dr.iastate.edu:etd-2734","is_oa":false,"landing_page_url":"https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=2734&amp;amp;context=etd","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Graduate Theses and Dissertations","raw_type":"text"},{"id":"pmh:oai:lib.dr.iastate.edu:stat_las_preprints-1025","is_oa":false,"landing_page_url":"https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1025&context=stat_las_preprints","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Statistics Preprints","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.142.8623","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.8623","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.stat.iastate.edu/preprint/articles/2005-04.pdf","raw_type":"text"},{"id":"pmh:oai:dr.lib.iastate.edu:20.500.12876/90305","is_oa":false,"landing_page_url":"https://dr.lib.iastate.edu/handle/20.500.12876/90305","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"10.1198/004017008000000091","raw_type":"Text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W74412329","https://openalex.org/W196756148","https://openalex.org/W1494478641","https://openalex.org/W1499164964","https://openalex.org/W1506354754","https://openalex.org/W1975208012","https://openalex.org/W1995227999","https://openalex.org/W1995945562","https://openalex.org/W1999292989","https://openalex.org/W2056099894","https://openalex.org/W2059770937","https://openalex.org/W2067244657","https://openalex.org/W2078184109","https://openalex.org/W2081502844","https://openalex.org/W2086331722","https://openalex.org/W2106842153","https://openalex.org/W2151038992","https://openalex.org/W2319384619","https://openalex.org/W2623408274","https://openalex.org/W2796291475","https://openalex.org/W2798023765","https://openalex.org/W4232802167","https://openalex.org/W4238275581"],"related_works":["https://openalex.org/W2363656491","https://openalex.org/W4376988598","https://openalex.org/W4388007941","https://openalex.org/W4243114048","https://openalex.org/W2884149040","https://openalex.org/W4237896776","https://openalex.org/W2159198570","https://openalex.org/W1581143638","https://openalex.org/W2111545434","https://openalex.org/W4381052368"],"abstract_inverted_index":{"Many":[0],"systems":[1],"experience":[2],"recurrent":[3],"events.":[4,21],"Recurrence":[5],"data":[6,29,41,69,137,216],"are":[7,25,42,217,282,324,335,461,515],"collected":[8],"to":[9,36,97,106,168,284,310,315,327,422,474,521],"analyze":[10,98],"quantities":[11],"of":[12,20,23,132,233,244,343,352,358,371,383,391,398,409,418,441,453,480,484,490],"interest,":[13],"such":[14,249],"as":[15,308],"the":[16,72,84,89,108,119,130,136,141,147,157,170,179,186,189,195,200,208,231,234,241,257,261,264,278,285,297,312,341,350,356,384,389,396,416,442,451,454,458,471,478,482,488,498,502,510,518],"mean":[17,109],"cumulative":[18,110],"number":[19,351,357,390,397,479,483],"Methods":[22],"analysis":[24,212],"available":[26],"for":[27,74,118,146,211,256,348,381,439,501,517],"recurrence":[28,40,68,79,100,124,152,174,215,258,265],"with":[30,48,77,122,150,172,213,373,411,492],"left":[31],"and/or":[32,395,403],"right":[33],"censoring.":[34],"Due":[35],"practical":[37],"constraints,":[38],"however,":[39,332],"sometimes":[43],"recorded":[44],"only":[45],"in":[46,50,135,321,337,447,462],"windows,":[47],"gaps":[49],"between.":[51],"Nelson":[52],"(2003,":[53],"page":[54],"75)":[55],"gives":[56],"one":[57],"example,":[58,349],"and":[59,95,102,114,126,163,199,207,271,363,450,457,487,504,508,512,524],"Chapter":[60,176,293,322,448,463,465],"2":[61,177,294,323],"describes":[62],"two":[63,279],"other":[64],"applications":[65],"that":[66,156,304,514],"window-observation":[67,78,99,123,151,173,214],"arise.":[70],"With":[71],"need":[73],"analytical":[75],"methods":[76],"data,":[80,101,125,259],"our":[81,103],"research":[82,154,428],"achieves":[83],"following":[85],"three":[86],"objectives:\\n(1).":[87],"Extend":[88],"existing":[90,158],"statistical":[91,159],"methods,":[92,160],"both":[93,161],"nonparametric":[94,162],"parametric,":[96,164],"focus":[104],"is":[105,138,237,247,346,354,361,365,393,401,405],"estimate":[107,169],"function":[111],"(MCF).\\n(2).":[112],"Study":[113],"compare":[115],"CI":[116,376,420,437,472],"procedures":[117,377,438,473],"MCF":[120,148,171,183,313,318,385,444,506,519],"estimators":[121,149,281,314,319,445,520],"make":[127],"recommendations":[128],"when":[129,251,388],"amount":[131,342,370,408,489],"observed":[133,344,359,399],"information":[134,345],"small.\\n(3).":[139],"Establish":[140],"asymptotic":[142,499],"(i.e.,":[143],"large-sample)":[144],"properties":[145,500],"data.\\nOur":[153],"shows":[155],"can":[165,305],"be":[166,228,306,522],"extended":[167],"data.":[175],"provides":[178],"details":[180,452],"on":[181,263,435,470,477],"four":[182,317,443],"estimators,":[184,507],"including":[185],"NP":[187,205,221,286,503],"estimator,":[188,194,198,287],"nonhomogeneous":[190],"Poisson":[191],"process":[192],"(NHPP)":[193],"local":[196],"hybrid":[197,202,280],"NHPP":[201,209,505],"estimator.":[203],"The":[204,220],"estimator":[206,210,222],"straight-forward":[218],"extensions.":[219],"requires":[223],"minimum":[224],"assumptions,":[225],"but":[226],"will":[227],"inconsistent":[229],"if":[230],"size":[232],"risk":[235],"set":[236],"not":[238],"positive":[239],"over":[240],"entire":[242],"period":[243],"interest.":[245],"There":[246],"no":[248,366],"difficulty":[250],"using":[252],"a":[253,301,425],"parametric":[254],"model":[255],"yet":[260],"assumption":[262],"rate":[266],"form":[267],"needs":[268],"careful":[269],"diagnoses":[270],"checking.":[272],"When":[273,340],"risk-set-size-zero":[274],"(RSSZ)":[275],"intervals":[276,334],"exist,":[277],"alternatives":[283],"which":[288,419],"generates":[289],"downwardly":[290],"biased":[291],"estimates.":[292],"also":[295,467],"presents":[296],"summary":[298,459],"results":[299,380,460],"from":[300],"simulation":[302,433,455],"study":[303,434],"used":[307],"references":[309],"select":[311],"use.\\nThe":[316],"described":[320,446],"relatively":[325,406],"easy":[326],"calculate.":[328],"Besides":[329],"point":[330],"estimates,":[331],"confidence":[333],"useful":[336],"many":[338],"applications.":[339],"large,":[347,355,362],"units":[353,392],"recurrences":[360,400,485],"there":[364,404],"or":[367,413,494],"very":[368],"small":[369],"time":[372,410,491],"RSSZ,":[374],"various":[375],"generate":[378],"similar":[379],"each":[382,440],"estimators.":[386],"However,":[387],"small,":[394,402],"large":[407],"RSSZ":[412,493],"risk-set-size-one":[414],"(RSSONE),":[415],"choice":[417],"procedure":[421],"use":[423,475],"makes":[424,468],"difference.":[426],"Our":[427],"carries":[429],"out":[430],"an":[431],"extensive":[432],"five":[436],"2,":[449],"studies":[456],"3.":[464],"3":[466],"suggestions":[469],"based":[476],"units,":[481],"observed,":[486],"RSSONE.\\nChapter":[495],"4":[496],"establishes":[497],"outlines":[509],"assumptions":[511],"conditions":[513],"needed":[516],"consistent":[523],"asymptotically":[525],"normal.":[526]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
