{"id":"https://openalex.org/W2963125570","doi":"https://doi.org/10.1080/03610918.2019.1626885","title":"A flexible spatial autoregressive modelling framework for mixed covariates of multiple data types","display_name":"A flexible spatial autoregressive modelling framework for mixed covariates of multiple data types","publication_year":2019,"publication_date":"2019-06-17","ids":{"openalex":"https://openalex.org/W2963125570","doi":"https://doi.org/10.1080/03610918.2019.1626885","mag":"2963125570"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1626885","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1626885","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/A5101791243","display_name":"Huiwen Wang","orcid":"https://orcid.org/0000-0001-7256-636X"},"institutions":[{"id":"https://openalex.org/I4210165198","display_name":"Beijing Advanced Sciences and Innovation Center","ror":"https://ror.org/05qm21180","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165198"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiwen Wang","raw_affiliation_strings":["Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China","School of Economics and Management, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I4210165198","https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Economics and Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011404110","display_name":"Tingting Huang","orcid":"https://orcid.org/0000-0002-6310-9797"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingting Huang","raw_affiliation_strings":["Beijing Key Laboratory of Emergence Support Simulation Technologies for City Operations, Beijing, China","School of Economics and Management, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Emergence Support Simulation Technologies for City Operations, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Economics and Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100406258","display_name":"Shanshan Wang","orcid":"https://orcid.org/0000-0002-7205-3844"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shanshan Wang","raw_affiliation_strings":["Beijing Key Laboratory of Emergence Support Simulation Technologies for City Operations, Beijing, China","School of Economics and Management, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Emergence Support Simulation Technologies for City Operations, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"School of Economics and Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100406258"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.4417,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77703984,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"50","issue":"11","first_page":"3498","last_page":"3515"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9993000030517578,"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":0.9993000030517578,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11014","display_name":"Regional Economics and Spatial Analysis","score":0.9635999798774719,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.7899379730224609},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7413625121116638},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6654013991355896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5427274107933044},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4839332699775696},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.479484885931015},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.46941623091697693},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4088710844516754},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36688387393951416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34138327836990356},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32558611035346985},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2813882827758789},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26288747787475586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2358551025390625}],"concepts":[{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.7899379730224609},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7413625121116638},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6654013991355896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5427274107933044},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4839332699775696},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.479484885931015},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.46941623091697693},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4088710844516754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36688387393951416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34138327836990356},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32558611035346985},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2813882827758789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26288747787475586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2358551025390625},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1626885","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1626885","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":[],"awards":[{"id":"https://openalex.org/G5284813800","display_name":null,"funder_award_id":"71420107025","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7299032961","display_name":null,"funder_award_id":"11701023","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1486960811","https://openalex.org/W1981145803","https://openalex.org/W1981551269","https://openalex.org/W1989765480","https://openalex.org/W1991449081","https://openalex.org/W1995775640","https://openalex.org/W2009854401","https://openalex.org/W2013624176","https://openalex.org/W2047114443","https://openalex.org/W2061309172","https://openalex.org/W2071673199","https://openalex.org/W2073404504","https://openalex.org/W2075346238","https://openalex.org/W2117420831","https://openalex.org/W2143220485","https://openalex.org/W2144751663","https://openalex.org/W2153796345","https://openalex.org/W2506906012","https://openalex.org/W2767460419","https://openalex.org/W2779734446","https://openalex.org/W2782896918","https://openalex.org/W2964115906","https://openalex.org/W3101449523","https://openalex.org/W4205462863","https://openalex.org/W4292156489","https://openalex.org/W4301651410"],"related_works":["https://openalex.org/W2985746494","https://openalex.org/W4206042385","https://openalex.org/W2511384863","https://openalex.org/W2096089271","https://openalex.org/W2923628599","https://openalex.org/W2014100433","https://openalex.org/W2051519658","https://openalex.org/W2994787386","https://openalex.org/W2002304499","https://openalex.org/W2112143119"],"abstract_inverted_index":{"Mixed":[0],"spatial":[1],"autoregressive":[2],"(SAR)":[3],"models":[4,43,75,79],"with":[5,44,80],"numerical":[6],"covariates":[7],"have":[8],"been":[9],"well":[10],"studied.":[11],"However,":[12],"as":[13,17],"non-numerical":[14],"data,":[15,22],"such":[16],"functional":[18,73,97],"data":[19,46],"and":[20,28,34,59,76,107],"compositional":[21,58,77],"receive":[23],"substantial":[24],"amounts":[25],"of":[26,55,71,120,133],"attention":[27],"are":[29],"applied":[30],"to":[31,39,129],"economics,":[32],"medicine":[33],"meteorology,":[35],"it":[36],"becomes":[37],"necessary":[38],"develop":[40,85],"flexible":[41],"SAR":[42,63],"multiple":[45],"types.":[47],"In":[48],"this":[49],"article,":[50],"we":[51,84],"integrate":[52],"three":[53],"types":[54],"covariates,":[56],"functional,":[57],"numerical,":[60],"in":[61],"an":[62,86],"model.":[64,136],"The":[65],"new":[66],"model":[67],"has":[68],"the":[69,90,102,108,118,121,131,134],"merits":[70],"classical":[72],"linear":[74,78],"scalar":[81],"responses.":[82],"Moreover,":[83],"estimation":[87,111],"method":[88],"for":[89],"proposed":[91,135],"model,":[92],"which":[93],"is":[94,126],"based":[95],"on":[96],"principal":[98],"component":[99],"analysis":[100],"(FPCA),":[101],"isometric":[103],"logratio":[104],"(ilr)":[105],"transformation":[106],"maximum":[109],"likelihood":[110],"(MLE)":[112],"method.":[113],"Monte":[114],"Carlo":[115],"experiments":[116],"demonstrate":[117],"effectiveness":[119],"estimators.":[122],"A":[123],"real":[124],"dataset":[125],"also":[127],"used":[128],"illustrate":[130],"utility":[132]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}