{"id":"https://openalex.org/W3082016562","doi":"https://doi.org/10.1080/10618600.2020.1814789","title":"Improving Bayesian Local Spatial Models in Large Datasets","display_name":"Improving Bayesian Local Spatial Models in Large Datasets","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3082016562","doi":"https://doi.org/10.1080/10618600.2020.1814789","mag":"3082016562"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2020.1814789","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2020.1814789","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Improving_Bayesian_Local_Spatial_Models_in_Large_Datasets/24814683","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102827197","display_name":"Amanda Lenzi","orcid":null},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Amanda Lenzi","raw_affiliation_strings":["Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;"],"affiliations":[{"raw_affiliation_string":"Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048011656","display_name":"Stefano Castruccio","orcid":"https://orcid.org/0000-0002-6728-965X"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stefano Castruccio","raw_affiliation_strings":["Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN"],"affiliations":[{"raw_affiliation_string":"Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061250326","display_name":"H\u00e5vard Rue","orcid":"https://orcid.org/0000-0002-5833-2011"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"H\u00e5vard Rue","raw_affiliation_strings":["Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;"],"affiliations":[{"raw_affiliation_string":"Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027166101","display_name":"Marc G. Genton","orcid":"https://orcid.org/0000-0001-6467-2998"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Marc G. Genton","raw_affiliation_strings":["Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;"],"affiliations":[{"raw_affiliation_string":"Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;","institution_ids":["https://openalex.org/I71920554"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102827197"],"corresponding_institution_ids":["https://openalex.org/I71920554"],"apc_list":null,"apc_paid":null,"fwci":0.2913,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55567554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"30","issue":"2","first_page":"349","last_page":"359"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11588","display_name":"Atmospheric and Environmental Gas Dynamics","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9882000088691711,"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/variance","display_name":"Variance (accounting)","score":0.6924939155578613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6602630615234375},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5555678009986877},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4789300858974457},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.477373331785202},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44157376885414124},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3884245455265045},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3760557174682617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22839239239692688},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20733803510665894}],"concepts":[{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6924939155578613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6602630615234375},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5555678009986877},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4789300858974457},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.477373331785202},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44157376885414124},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3884245455265045},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3760557174682617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22839239239692688},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20733803510665894},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10618600.2020.1814789","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2020.1814789","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/24814683","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Improving_Bayesian_Local_Spatial_Models_in_Large_Datasets/24814683","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:repository.kaust.edu.sa:10754/660681","is_oa":false,"landing_page_url":"http://hdl.handle.net/10754/660681","pdf_url":null,"source":{"id":"https://openalex.org/S4306401596","display_name":"King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71920554","host_organization_name":"King Abdullah University of Science and Technology","host_organization_lineage":["https://openalex.org/I71920554"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/24814683","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Improving_Bayesian_Local_Spatial_Models_in_Large_Datasets/24814683","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W134473611","https://openalex.org/W143236119","https://openalex.org/W1487139063","https://openalex.org/W1520585082","https://openalex.org/W1837874438","https://openalex.org/W1914588449","https://openalex.org/W1995001525","https://openalex.org/W1997999159","https://openalex.org/W1998290124","https://openalex.org/W2005938337","https://openalex.org/W2007392640","https://openalex.org/W2027081786","https://openalex.org/W2037516052","https://openalex.org/W2040635790","https://openalex.org/W2040850257","https://openalex.org/W2050497240","https://openalex.org/W2051416171","https://openalex.org/W2056366968","https://openalex.org/W2067911981","https://openalex.org/W2144898279","https://openalex.org/W2151115007","https://openalex.org/W2165799067","https://openalex.org/W2340515955","https://openalex.org/W2567289819","https://openalex.org/W2765431235","https://openalex.org/W2902287106","https://openalex.org/W2922527678","https://openalex.org/W2962756992","https://openalex.org/W2962853524","https://openalex.org/W2962980151","https://openalex.org/W2963282124","https://openalex.org/W2963394916","https://openalex.org/W2964139940","https://openalex.org/W2964191000","https://openalex.org/W2964225085","https://openalex.org/W3021788325","https://openalex.org/W3029079406","https://openalex.org/W3037079691","https://openalex.org/W3088111924","https://openalex.org/W3100755667","https://openalex.org/W3105899516","https://openalex.org/W4300223101"],"related_works":["https://openalex.org/W2372267530","https://openalex.org/W2969189870","https://openalex.org/W3015855446","https://openalex.org/W4303857162","https://openalex.org/W2965643117","https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W2010643158","https://openalex.org/W3049691116"],"abstract_inverted_index":{"Environmental":[0],"processes":[1,17],"resolved":[2],"at":[3],"a":[4,61,114,174],"sufficiently":[5],"small":[6,74,92],"scale":[7],"in":[8,102,156,160],"space":[9],"and":[10,23,70,80,87],"time":[11],"inevitably":[12],"display":[13],"nonstationary":[14],"behavior.":[15],"Such":[16],"are":[18,94,106,135,190],"both":[19,84],"challenging":[20],"to":[21,44,96,108,137,144],"model":[22],"computationally":[24],"expensive":[25],"when":[26],"the":[27,35,48,53,85,99,110,126,129,139,145,152],"data":[28,181],"size":[29,54],"is":[30,58],"large.":[31],"Instead":[32],"of":[33,47,52,55,90,128,176],"modeling":[34,86],"global":[36],"non-stationarity":[37],"explicitly,":[38],"local":[39],"models":[40],"can":[41],"be":[42],"applied":[43],"disjoint":[45],"regions":[46,57,65,75,93,105,123],"domain.":[49],"The":[50,154],"choice":[51],"these":[56],"dictated":[59],"by":[60,150],"bias-variance":[62],"trade-off;":[63],"large":[64,104],"will":[66,76],"have":[67,77],"smaller":[68,81,122],"variance":[69,79,130],"larger":[71],"bias,":[72],"whereas":[73],"higher":[78],"bias.":[82],"From":[83],"computational":[88],"point":[89],"view,":[91],"preferable":[95],"better":[97],"accommodate":[98],"non-stationarity.":[100],"However,":[101],"practice,":[103],"necessary":[107],"control":[109],"variance.":[111],"We":[112,134,168],"propose":[113],"novel":[115],"Bayesian":[116],"three-step":[117],"approach":[118,172],"that":[119,131],"allows":[120],"for":[121,187],"without":[124,147],"compromising":[125],"increase":[127],"would":[132],"follow.":[133],"able":[136],"propagate":[138],"uncertainty":[140],"from":[141],"one":[142],"step":[143],"next":[146],"issues":[148],"caused":[149],"reusing":[151],"data.":[153],"improvement":[155],"inference":[157],"also":[158],"results":[159],"improved":[161],"prediction,":[162],"as":[163],"our":[164],"simulated":[165,177],"example":[166],"shows.":[167],"illustrate":[169],"this":[170,188],"new":[171],"on":[173],"dataset":[175],"high-resolution":[178],"wind":[179],"speed":[180],"over":[182],"Saudi":[183],"Arabia.":[184],"Supplemental":[185],"files":[186],"article":[189],"available":[191],"online.":[192]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}