{"id":"https://openalex.org/W4285007464","doi":"https://doi.org/10.1080/03610918.2022.2093373","title":"Statistical inference of dependent competing risks from Marshall\u2013Olkin bivariate Burr-XII distribution under complex censoring","display_name":"Statistical inference of dependent competing risks from Marshall\u2013Olkin bivariate Burr-XII distribution under complex censoring","publication_year":2022,"publication_date":"2022-07-11","ids":{"openalex":"https://openalex.org/W4285007464","doi":"https://doi.org/10.1080/03610918.2022.2093373"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2093373","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2093373","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":["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/A5003064587","display_name":"Yajie Tian","orcid":"https://orcid.org/0000-0001-9641-3309"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yajie Tian","raw_affiliation_strings":["School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053074333","display_name":"Wenhao Gui","orcid":"https://orcid.org/0000-0003-4318-1780"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenhao Gui","raw_affiliation_strings":["School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4318-1780","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5053074333"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":2.3281,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89236801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"53","issue":"6","first_page":"2988","last_page":"3012"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9998999834060669,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9998999834060669,"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9901999831199646,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9769999980926514,"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":0.6964994668960571},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.6421999931335449},{"id":"https://openalex.org/keywords/cauchy-distribution","display_name":"Cauchy distribution","score":0.6165395379066467},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5965921878814697},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.5510146021842957},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.547921895980835},{"id":"https://openalex.org/keywords/log-normal-distribution","display_name":"Log-normal distribution","score":0.54436856508255},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5317923426628113},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4863343834877014},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4623924493789673},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.42809563875198364},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4210337996482849},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2819277346134186}],"concepts":[{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.6964994668960571},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.6421999931335449},{"id":"https://openalex.org/C49344536","wikidata":"https://www.wikidata.org/wiki/Q726441","display_name":"Cauchy distribution","level":2,"score":0.6165395379066467},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5965921878814697},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.5510146021842957},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.547921895980835},{"id":"https://openalex.org/C151620405","wikidata":"https://www.wikidata.org/wiki/Q826116","display_name":"Log-normal distribution","level":2,"score":0.54436856508255},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5317923426628113},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4863343834877014},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4623924493789673},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.42809563875198364},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4210337996482849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2819277346134186},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2093373","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2093373","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.550000011920929,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1971846058","https://openalex.org/W1974208482","https://openalex.org/W2017596715","https://openalex.org/W2019136143","https://openalex.org/W2025391286","https://openalex.org/W2048509646","https://openalex.org/W2048832652","https://openalex.org/W2048881733","https://openalex.org/W2054228918","https://openalex.org/W2064362848","https://openalex.org/W2072430699","https://openalex.org/W2074364289","https://openalex.org/W2126391818","https://openalex.org/W2148440732","https://openalex.org/W2177452242","https://openalex.org/W2232897565","https://openalex.org/W2436523376","https://openalex.org/W2493671571","https://openalex.org/W2529846021","https://openalex.org/W2541779892","https://openalex.org/W2583057386","https://openalex.org/W2912133652","https://openalex.org/W2999738294","https://openalex.org/W3047007589","https://openalex.org/W3084254303","https://openalex.org/W3111481980","https://openalex.org/W3120609532","https://openalex.org/W3126622935","https://openalex.org/W3138719287","https://openalex.org/W3162044869","https://openalex.org/W3165493093","https://openalex.org/W3192700151","https://openalex.org/W4299419703"],"related_works":["https://openalex.org/W2587771768","https://openalex.org/W1592683135","https://openalex.org/W1887515435","https://openalex.org/W2096369821","https://openalex.org/W2051221975","https://openalex.org/W2804911516","https://openalex.org/W1987165598","https://openalex.org/W2093210265","https://openalex.org/W2398033131","https://openalex.org/W1583888688"],"abstract_inverted_index":{"Dealing":[0],"with":[1,25,85,91],"competing":[2,23,56],"risks":[3,24,57],"is":[4,18,48,112],"an":[5],"important":[6],"problem":[7],"in":[8,29,59],"reliability":[9],"analysis":[10,58],"and":[11,68,79,94,134],"attracts":[12],"much":[13],"attention":[14],"from":[15],"scholars.":[16],"It":[17],"more":[19],"practical":[20],"to":[21,50,100,114],"consider":[22],"dependent":[26,55],"failure":[27],"causes":[28],"reality.":[30],"In":[31,106],"this":[32],"article,":[33],"statistical":[34],"inference":[35],"of":[36,54,73,81,104,119,126],"the":[37,52,60,116,124],"Marshall\u2013Olkin":[38],"bivariate":[39],"Burr-XII":[40],"distribution":[41],"under":[42],"adaptive":[43],"type-II":[44],"progressive":[45],"hybrid":[46],"censoring":[47],"discussed":[49],"show":[51],"procedure":[53],"complex":[61],"data":[62,136],"structure.":[63],"The":[64,77,88],"maximum":[65],"likelihood":[66],"estimation":[67,103],"lognormal":[69],"approximation":[70],"confidence":[71],"intervals":[72],"parameters":[74],"are":[75,83,97],"computed.":[76],"existence":[78],"uniqueness":[80],"solutions":[82],"proved":[84],"Cauchy-Schwarz":[86],"inequality.":[87],"Bayesian":[89],"method":[90],"Gamma-Dirichlet":[92],"prior":[93],"Metropolis-Hastings":[95],"algorithm":[96],"further":[98],"considered":[99],"find":[101],"satisfied":[102],"parameters.":[105],"addition,":[107],"dynamic":[108],"cumulative":[109],"residual":[110],"entropy":[111],"derived":[113],"quantify":[115],"information":[117],"uncertainty":[118],"data.":[120],"We":[121],"finally":[122],"compare":[123],"performance":[125],"various":[127],"methods":[128],"by":[129],"conducting":[130],"a":[131],"simulation":[132],"study":[133],"real":[135],"analysis.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
