{"id":"https://openalex.org/W4388319865","doi":"https://doi.org/10.1093/oso/9780198526155.003.0003","title":"Hierarchical Multivariate CAR Models for Spatio-Temporally Correlated Survival Data","display_name":"Hierarchical Multivariate CAR Models for Spatio-Temporally Correlated Survival Data","publication_year":2003,"publication_date":"2003-07-03","ids":{"openalex":"https://openalex.org/W4388319865","doi":"https://doi.org/10.1093/oso/9780198526155.003.0003"},"language":"en","primary_location":{"id":"doi:10.1093/oso/9780198526155.003.0003","doi":"https://doi.org/10.1093/oso/9780198526155.003.0003","is_oa":false,"landing_page_url":"https://doi.org/10.1093/oso/9780198526155.003.0003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bayesian Statistics 7","raw_type":"book-chapter"},"volume":{"id":"https://openalex.org/W4388290495","display_name":"Bayesian Statistics 7"},"type":"book-chapter","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/A5012243539","display_name":"Bradley P. Carlin","orcid":"https://orcid.org/0000-0002-0684-8753","observed_orcids":["https://orcid.org/0000-0002-0684-8753"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bradley P Carlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5069620117","display_name":"Sudipto Banerjee","orcid":"https://orcid.org/0000-0002-2239-208X","observed_orcids":["https://orcid.org/0000-0002-2239-208X"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sudipto Banerjee","raw_affiliation_strings":["University of Minnesota, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.504,"has_fulltext":false,"cited_by_count":96,"citation_normalized_percentile":{"value":0.98712918,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"45","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.002199999988079071,"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/conditional-autoregressive-model","display_name":"conditional autoregressive model","score":0.8119999766349792},{"id":"https://openalex.org/keywords/hierarchical-models","display_name":"hierarchical models","score":0.6639999747276306},{"id":"https://openalex.org/keywords/spatiotemporal-correlation","display_name":"spatio-temporal correlation","score":0.9319999814033508},{"id":"https://openalex.org/keywords/survival-data","display_name":"survival data","score":0.953000009059906},{"id":"https://openalex.org/keywords/georeferenced-records","display_name":"georeferenced records","score":0.847000002861023},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5299999713897705},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8629999756813049}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7588323950767517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125157117843628},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6202079057693481},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5766239166259766},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5105425119400024},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5045455694198608},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.49656206369400024},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46362069249153137},{"id":"https://openalex.org/C75145180","wikidata":"https://www.wikidata.org/wiki/Q772007","display_name":"Georeference","level":2,"score":0.43467313051223755},{"id":"https://openalex.org/C176222170","wikidata":"https://www.wikidata.org/wiki/Q5157340","display_name":"Computational statistics","level":2,"score":0.4131457805633545},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.411998450756073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2990592122077942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2561069130897522},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1831282079219818},{"id":"https://openalex.org/C100970517","wikidata":"https://www.wikidata.org/wiki/Q52107","display_name":"Physical geography","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/oso/9780198526155.003.0003","doi":"https://doi.org/10.1093/oso/9780198526155.003.0003","is_oa":false,"landing_page_url":"https://doi.org/10.1093/oso/9780198526155.003.0003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bayesian Statistics 7","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7096813696","https://openalex.org/W7098886713","https://openalex.org/W2161132263","https://openalex.org/W2261809275","https://openalex.org/W1981043831","https://openalex.org/W2326501207","https://openalex.org/W2600076993","https://openalex.org/W3095107819","https://openalex.org/W2055663307","https://openalex.org/W1853715423"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"analysis":[2,66],"of":[3,13,51,69,96],"spatially":[4,129],"referenced":[5],"data":[6,71,79,119],"has":[7],"been":[8,30],"an":[9,48],"increasingly":[10],"active":[11],"area":[12],"both":[14],"methodological":[15],"and":[16,27,38,67,126],"applied":[17],"statistical":[18],"research.":[19],"As":[20],"with":[21,43],"many":[22],"fields,":[23],"advances":[24],"in":[25,100,111],"computing":[26],"software":[28],"have":[29,63],"largely":[31],"responsible.":[32],"Modern":[33],"database":[34],"engines,":[35],"often":[36],"widely":[37],"publicly":[39],"available":[40],"to":[41,76],"anyone":[42],"a":[44,82,101],"web":[45],"browser,":[46],"provide":[47],"enormous":[49],"supply":[50],"georeferenced":[52],"data.":[53],"Sophisticated":[54],"computer":[55],"programs":[56],"known":[57],"as":[58],"geographic":[59],"information":[60],"systems":[61],"(GISs)":[62],"revolutionized":[64],"the":[65,94],"display":[68],"such":[70],"sets,":[72],"through":[73],"their":[74],"ability":[75],"\u201clayer\u201d":[77],"multiple":[78],"sources":[80],"over":[81],"common":[83],"study":[84],"area.":[85],"Finally,":[86],"Markov":[87],"chain":[88],"Monte":[89],"Carlo":[90],"(MCMC)":[91],"algorithms":[92],"enable":[93],"fitting":[95],"complex":[97,113],"hierarchical":[98],"models":[99],"Bayesian":[102],"framework,":[103],"permitting":[104],"full":[105],"posterior":[106],"inference":[107],"for":[108],"underlying":[109],"parameters":[110],"even":[112,128],"model":[114],"settings":[115],"(e.g.,":[116],"those":[117],"involving":[118],"that":[120],"are":[121],"highly":[122],"multivariate,":[123],"temporally":[124,131],"correlated,":[125],"perhaps":[127],"or":[130],"misaligned).":[132]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":4}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-11-04T00:00:00"}