{"id":"https://openalex.org/W4253553965","doi":"https://doi.org/10.1080/00401706.1999.10485593","title":"Multivariate Zero-Inflated Poisson Models and Their Applications","display_name":"Multivariate Zero-Inflated Poisson Models and Their Applications","publication_year":1999,"publication_date":"1999-02-01","ids":{"openalex":"https://openalex.org/W4253553965","doi":"https://doi.org/10.1080/00401706.1999.10485593"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.1999.10485593","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.1999.10485593","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/A5086251816","display_name":"Chin\u2010Shang Li","orcid":"https://orcid.org/0000-0002-0054-4476"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chin-Shang Li","raw_affiliation_strings":["Department of Statistics , North Carolina State University , Raleigh , NC , 27695-8203 E-mail: Li@stat.ncsu.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics , North Carolina State University , Raleigh , NC , 27695-8203 E-mail: Li@stat.ncsu.edu","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033869327","display_name":"Jye\u2010Chyi Lu","orcid":"https://orcid.org/0000-0001-6628-1544"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jye-Chyi Lu","raw_affiliation_strings":["Department of Statistics , North Carolina State University , Raleigh , NC , 27695-8203 E-mail: Li@stat.ncsu.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics , North Carolina State University , Raleigh , NC , 27695-8203 E-mail: Li@stat.ncsu.edu","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385846","display_name":"Jinho Park","orcid":"https://orcid.org/0000-0001-8223-3390"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinho Park","raw_affiliation_strings":["Department of Statistics , North Carolina State University , Raleigh , NC , 27695-8203 E-mail: Li@stat.ncsu.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics , North Carolina State University , Raleigh , NC , 27695-8203 E-mail: Li@stat.ncsu.edu","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052027699","display_name":"Kyungmoo Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I4210129133","display_name":"Taegu Science University","ror":"https://ror.org/036rtm992","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210129133"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyungmoo Kim","raw_affiliation_strings":["Department of Statistics , Taegu University , Taegu , Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics , Taegu University , Taegu , Korea","institution_ids":["https://openalex.org/I4210129133"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023638300","display_name":"Paul A. Brinkley","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090916","display_name":"Triangle","ror":"https://ror.org/00fhbr831","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210090916"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul A. Brinkley","raw_affiliation_strings":["Northern Telecom Research Triangle Park , Raleigh , NC , 27709"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northern Telecom Research Triangle Park , Raleigh , NC , 27709","institution_ids":["https://openalex.org/I4210090916"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083978667","display_name":"J.P. Peterson","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090916","display_name":"Triangle","ror":"https://ror.org/00fhbr831","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210090916"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John P. Peterson","raw_affiliation_strings":["Northern Telecom Research Triangle Park , Raleigh , NC , 27709"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northern Telecom Research Triangle Park , Raleigh , NC , 27709","institution_ids":["https://openalex.org/I4210090916"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2691,"has_fulltext":false,"cited_by_count":125,"citation_normalized_percentile":{"value":0.86013677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"41","issue":"1","first_page":"29","last_page":"38"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.7393485307693481},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7010838985443115},{"id":"https://openalex.org/keywords/zero-inflated-model","display_name":"Zero-inflated model","score":0.6414467096328735},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.6042728424072266},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.5435760021209717},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.520839512348175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5170748829841614},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.45548170804977417},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.44934332370758057},{"id":"https://openalex.org/keywords/poisson-regression","display_name":"Poisson regression","score":0.3455345630645752},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3335411846637726},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3302844762802124}],"concepts":[{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.7393485307693481},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7010838985443115},{"id":"https://openalex.org/C88721176","wikidata":"https://www.wikidata.org/wiki/Q966010","display_name":"Zero-inflated model","level":4,"score":0.6414467096328735},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.6042728424072266},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.5435760021209717},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.520839512348175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5170748829841614},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.45548170804977417},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44934332370758057},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.3455345630645752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3335411846637726},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3302844762802124},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.1999.10485593","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.1999.10485593","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1538127276","https://openalex.org/W1988204486","https://openalex.org/W1989670556","https://openalex.org/W2077724217","https://openalex.org/W2109810869","https://openalex.org/W2109856979","https://openalex.org/W2113153993","https://openalex.org/W2114013702","https://openalex.org/W2155599477","https://openalex.org/W2614237344","https://openalex.org/W4252821048"],"related_works":["https://openalex.org/W2509788866","https://openalex.org/W2350442714","https://openalex.org/W3121314510","https://openalex.org/W2503331259","https://openalex.org/W3134844154","https://openalex.org/W3096804274","https://openalex.org/W1590941618","https://openalex.org/W1975095546","https://openalex.org/W3200250056","https://openalex.org/W2150462512"],"abstract_inverted_index":{"The":[0],"zero-inflated":[1],"Poisson":[2],"(ZIP)":[3],"distribution":[4],"has":[5,80],"been":[6],"shown":[7],"to":[8,36,43,71],"be":[9,34],"useful":[10,35,113],"for":[11,118,122],"modeling":[12],"outcomes":[13],"of":[14,26,47,54,61,74],"manufacturing":[15,116],"processes":[16],"producing":[17],"numerous":[18],"defect-free":[19],"products.":[20],"When":[21],"there":[22],"are":[23,112],"several":[24],"types":[25,46,53],"defects,":[27],"the":[28,72,76,109],"multivariate":[29],"ZIP":[30],"(MZIP)":[31],"model":[32,94],"can":[33],"detect":[37],"specific":[38],"process":[39],"equipment":[40,105],"problems":[41],"and":[42,57,83,96,121],"reduce":[44],"multiple":[45],"defects":[48],"simultaneously.":[49],"This":[50],"article":[51],"proposes":[52],"MZIP":[55,63],"models":[56],"investigates":[58],"distributional":[59],"properties":[60],"an":[62],"model.":[64],"Finite-sample":[65],"simulation":[66],"studies":[67],"show":[68],"that,":[69],"compared":[70],"method":[73,79],"moments,":[75],"maximum":[77],"likelihood":[78],"smaller":[81],"bias":[82],"variance,":[84],"as":[85,87],"well":[86],"more":[88],"accurate":[89],"coverage":[90],"probability":[91],"in":[92,114],"estimating":[93],"parameters":[95],"zero-defect":[97],"probability.":[98],"Real-life":[99],"examples":[100],"from":[101],"a":[102,115],"major":[103],"electronic":[104],"manufacturer":[106],"illustrate":[107],"how":[108],"proposed":[110],"procedures":[111],"environment":[117],"equipment-fault":[119],"detection":[120],"covariate":[123],"effect":[124],"studies.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}