{"id":"https://openalex.org/W1902524874","doi":"https://doi.org/10.1080/03610918.2015.1065326","title":"Bootstrap Bartlett correction in inflated beta regression","display_name":"Bootstrap Bartlett correction in inflated beta regression","publication_year":2016,"publication_date":"2016-12-18","ids":{"openalex":"https://openalex.org/W1902524874","doi":"https://doi.org/10.1080/03610918.2015.1065326","mag":"1902524874"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2015.1065326","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1065326","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1506.03993","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"La\u00eds H. Loose","orcid":null},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"La\u00eds H. Loose","raw_affiliation_strings":["Departamento de Estat\u00edstica, Universidade Federal do Rio Grande do Norte, RN, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de Estat\u00edstica, Universidade Federal do Rio Grande do Norte, RN, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","author":{"id":null,"display_name":"F\u00e1bio M. Bayer","orcid":null},"institutions":[{"id":"https://openalex.org/I33501960","display_name":"Universidade Federal de Santa Maria","ror":"https://ror.org/01b78mz79","country_code":"BR","type":"education","lineage":["https://openalex.org/I33501960"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"F\u00e1bio M. Bayer","raw_affiliation_strings":["Departamento de Estat\u00edstica and LACESM, Universidade Federal de Santa Maria, RS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de Estat\u00edstica and LACESM, Universidade Federal de Santa Maria, RS, Brazil","institution_ids":["https://openalex.org/I33501960"]}]},{"author_position":"last","author":{"id":null,"display_name":"Tarciana L. Pereira","orcid":null},"institutions":[{"id":"https://openalex.org/I169045520","display_name":"Universidade Federal da Para\u00edba","ror":"https://ror.org/00p9vpz11","country_code":"BR","type":"education","lineage":["https://openalex.org/I169045520"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Tarciana L. Pereira","raw_affiliation_strings":["Departamento de Estat\u00edstica, Universidade Federal da Para\u00edba, PB, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de Estat\u00edstica, Universidade Federal da Para\u00edba, PB, Brazil","institution_ids":["https://openalex.org/I169045520"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33501960"],"apc_list":null,"apc_paid":null,"fwci":0.6996,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.72652257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"46","issue":"4","first_page":"2865","last_page":"2879"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.3488999903202057,"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":0.3488999903202057,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.24140000343322754,"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/T10136","display_name":"Statistical Methods and Inference","score":0.09120000153779984,"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/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.6866000294685364},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5898000001907349},{"id":"https://openalex.org/keywords/score-test","display_name":"Score test","score":0.4964999854564667},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.45190000534057617},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4275999963283539},{"id":"https://openalex.org/keywords/type-i-and-type-ii-errors","display_name":"Type I and type II errors","score":0.40939998626708984},{"id":"https://openalex.org/keywords/test-statistic","display_name":"Test statistic","score":0.39629998803138733},{"id":"https://openalex.org/keywords/likelihood-principle","display_name":"Likelihood principle","score":0.3944999873638153},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.38589999079704285}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6973999738693237},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.6866000294685364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6816999912261963},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5898000001907349},{"id":"https://openalex.org/C103463560","wikidata":"https://www.wikidata.org/wiki/Q4456449","display_name":"Score test","level":3,"score":0.4964999854564667},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.45190000534057617},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4275999963283539},{"id":"https://openalex.org/C40696583","wikidata":"https://www.wikidata.org/wiki/Q989120","display_name":"Type I and type II errors","level":2,"score":0.40939998626708984},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.39629998803138733},{"id":"https://openalex.org/C189559763","wikidata":"https://www.wikidata.org/wiki/Q13200161","display_name":"Likelihood principle","level":5,"score":0.3944999873638153},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C2781117939","wikidata":"https://www.wikidata.org/wiki/Q5374245","display_name":"Empirical likelihood","level":3,"score":0.3328000009059906},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.3222000002861023},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3203999996185303},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C61420037","wikidata":"https://www.wikidata.org/wiki/Q7316301","display_name":"Restricted maximum likelihood","level":3,"score":0.298799991607666},{"id":"https://openalex.org/C192914289","wikidata":"https://www.wikidata.org/wiki/Q165638","display_name":"Ratio test","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C2776174256","wikidata":"https://www.wikidata.org/wiki/Q830842","display_name":"BETA (programming language)","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C65660741","wikidata":"https://www.wikidata.org/wiki/Q3952743","display_name":"Score","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.2628999948501587}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/03610918.2015.1065326","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1065326","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1506.03993","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1506.03993","pdf_url":"https://arxiv.org/pdf/1506.03993","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1506.03993","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1506.03993","pdf_url":"https://arxiv.org/pdf/1506.03993","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,36,76,120],"inflated":[1,72],"beta":[2,73],"regression":[3,74],"model":[4],"aims":[5],"to":[6,47,64,105,156],"enable":[7],"the":[8,13,32,60,65,71,91,99,106,112,118,128,139,145,149,152],"modeling":[9],"of":[10,49,67,98,151],"responses":[11],"in":[12,51,70,117],"intervals":[14],"(0,":[15],"1],":[16],"[0,":[17,20],"1),":[18],"or":[19],"1].":[21],"In":[22,54],"this":[23,55,57],"model,":[24],"hypothesis":[25],"testing":[26],"is":[27,103,131,159],"often":[28],"performed":[29],"based":[30,126,137],"on":[31,127,138],"likelihood":[33,68,108,141],"ratio":[34,69,109,142],"statistic.":[35],"critical":[37],"values":[38],"are":[39],"obtained":[40],"from":[41],"asymptotic":[42],"approximations,":[43],"which":[44],"may":[45],"lead":[46],"distortions":[48],"size":[50],"small":[52],"samples.":[53],"sense,":[56],"article":[58],"proposes":[59],"bootstrap":[61],"Bartlett":[62],"correction":[63,130],"statistic":[66],"model.":[75],"proposed":[77,100,116,129],"adjustment":[78,114],"only":[79],"requires":[80],"a":[81],"simple":[82],"Monte":[83,88],"Carlo":[84,89],"simulation.":[85],"Through":[86],"extensive":[87],"simulations":[90],"finite":[92],"sample":[93],"performance":[94],"(size":[95],"and":[96,111,144],"power)":[97],"corrected":[101],"test":[102,110],"compared":[104],"usual":[107,140],"Skovgaard":[113,146],"already":[115],"literature.":[119],"numerical":[121],"results":[122],"evidence":[123],"that":[124,136],"inference":[125],"much":[132],"more":[133],"reliable":[134],"than":[135],"statistics":[143],"adjustment.":[147],"At":[148],"end":[150],"work,":[153],"an":[154],"application":[155],"real":[157],"data":[158],"also":[160],"presented.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}