{"id":"https://openalex.org/W4281916761","doi":"https://doi.org/10.5194/agile-giss-3-31-2022","title":"Spatially Varying Coefficient Regression with GAM Gaussian Process splines: GAM(e)-on","display_name":"Spatially Varying Coefficient Regression with GAM Gaussian Process splines: GAM(e)-on","publication_year":2022,"publication_date":"2022-06-10","ids":{"openalex":"https://openalex.org/W4281916761","doi":"https://doi.org/10.5194/agile-giss-3-31-2022"},"language":"en","primary_location":{"id":"doi:10.5194/agile-giss-3-31-2022","is_oa":true,"landing_page_url":"https://doi.org/10.5194/agile-giss-3-31-2022","pdf_url":"https://agile-giss.copernicus.org/articles/3/31/2022/agile-giss-3-31-2022.pdf","source":{"id":"https://openalex.org/S4210203054","display_name":"AGILE GIScience Series","issn_l":"2700-8150","issn":["2700-8150"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AGILE: GIScience Series","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://agile-giss.copernicus.org/articles/3/31/2022/agile-giss-3-31-2022.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012361423","display_name":"Alexis Comber","orcid":"https://orcid.org/0000-0002-3652-7846"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Alexis Comber","raw_affiliation_strings":["Leeds Institute for Data Analytics, University of Leeds, UK","School of Geography, University of Leeds, Leeds, UK"],"raw_orcid":"https://orcid.org/0000-0002-3652-7846","affiliations":[{"raw_affiliation_string":"Leeds Institute for Data Analytics, University of Leeds, UK","institution_ids":["https://openalex.org/I130828816"]},{"raw_affiliation_string":"School of Geography, University of Leeds, Leeds, UK","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060303150","display_name":"Paul G. Harris","orcid":"https://orcid.org/0000-0003-3647-5692"},"institutions":[{"id":"https://openalex.org/I2799553609","display_name":"Rothamsted Research","ror":"https://ror.org/0347fy350","country_code":"GB","type":"facility","lineage":["https://openalex.org/I2799553609","https://openalex.org/I2799693246","https://openalex.org/I4210087105"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Paul Harris","raw_affiliation_strings":["Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, UK","institution_ids":["https://openalex.org/I2799553609"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082892178","display_name":"Chris Brunsdon","orcid":"https://orcid.org/0000-0003-4254-1780"},"institutions":[{"id":"https://openalex.org/I157286207","display_name":"National University of Ireland, Maynooth","ror":"https://ror.org/048nfjm95","country_code":"IE","type":"education","lineage":["https://openalex.org/I157286207"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Chris Brunsdon","raw_affiliation_strings":["National Centre for Geocomputation, Maynooth University, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Centre for Geocomputation, Maynooth University, Ireland","institution_ids":["https://openalex.org/I157286207"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012361423"],"corresponding_institution_ids":["https://openalex.org/I130828816"],"apc_list":null,"apc_paid":null,"fwci":0.5057,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.56069877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9236999750137329,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9236999750137329,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6966065168380737},{"id":"https://openalex.org/keywords/generalized-additive-model","display_name":"Generalized additive model","score":0.6094801425933838},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5793857574462891},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5099824666976929},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4897744655609131},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47351861000061035},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.446618914604187},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.40599164366722107},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.38312166929244995},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.356642484664917},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3208984136581421},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16049706935882568}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6966065168380737},{"id":"https://openalex.org/C194648359","wikidata":"https://www.wikidata.org/wiki/Q3318054","display_name":"Generalized additive model","level":2,"score":0.6094801425933838},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5793857574462891},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5099824666976929},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4897744655609131},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47351861000061035},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.446618914604187},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.40599164366722107},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.38312166929244995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.356642484664917},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3208984136581421},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16049706935882568},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5194/agile-giss-3-31-2022","is_oa":true,"landing_page_url":"https://doi.org/10.5194/agile-giss-3-31-2022","pdf_url":"https://agile-giss.copernicus.org/articles/3/31/2022/agile-giss-3-31-2022.pdf","source":{"id":"https://openalex.org/S4210203054","display_name":"AGILE GIScience Series","issn_l":"2700-8150","issn":["2700-8150"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AGILE: GIScience Series","raw_type":"journal-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:208809","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.5194/agile-giss-3-31-2022","is_oa":true,"landing_page_url":"https://doi.org/10.5194/agile-giss-3-31-2022","pdf_url":"https://agile-giss.copernicus.org/articles/3/31/2022/agile-giss-3-31-2022.pdf","source":{"id":"https://openalex.org/S4210203054","display_name":"AGILE GIScience Series","issn_l":"2700-8150","issn":["2700-8150"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AGILE: GIScience Series","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8938594311","display_name":null,"funder_award_id":"UWB190190","funder_id":"https://openalex.org/F4320320004","funder_display_name":"British Academy"}],"funders":[{"id":"https://openalex.org/F4320320004","display_name":"British Academy","ror":"https://ror.org/0302b4677"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4281916761.pdf","grobid_xml":"https://content.openalex.org/works/W4281916761.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W20585472","https://openalex.org/W1250261183","https://openalex.org/W1973749534","https://openalex.org/W1990433983","https://openalex.org/W2047120335","https://openalex.org/W2747207142","https://openalex.org/W2767465154","https://openalex.org/W3048290715","https://openalex.org/W3122392460","https://openalex.org/W3216454795","https://openalex.org/W4229805950"],"related_works":["https://openalex.org/W2104174445","https://openalex.org/W2563155481","https://openalex.org/W3098068234","https://openalex.org/W1964389324","https://openalex.org/W1983892255","https://openalex.org/W3021457118","https://openalex.org/W2034939232","https://openalex.org/W4287073795","https://openalex.org/W2945250122","https://openalex.org/W3185162181"],"abstract_inverted_index":{"Abstract.":[0],"This":[1,92,110],"paper":[2,50],"describes":[3],"initial":[4,90],"work":[5,142],"exploring":[6],"GAM":[7,77],"Gaussian":[8],"Process":[9],"(GP)":[10],"splines":[11,61],"parameterised":[12],"by":[13,132],"observation":[14],"location,":[15],"as":[16],"a":[17],"geographical":[18],"varying":[19],"coefficient":[20,36],"model.":[21,91,109],"Similar":[22],"to":[23,42,126],"GWR,":[24],"this":[25],"approach":[26],"accommodates":[27],"process":[28,100,130],"spatial":[29],"heterogeneity":[30],"and":[31,62,79],"generates":[32],"spatially":[33],"distributed,":[34],"local":[35],"estimates.":[37],"These":[38],"can":[39,104],"be":[40,105],"mapped":[41],"indicate":[43],"the":[44,47,52,55,60,66,69,76,80,89,96,99,108,114,117,121,127,133],"nature":[45,67,97],"of":[46,54,68,98,120,129,138,140],"heterogeneity.":[48,71],"The":[49],"investigates":[51],"effect":[53],"smoothing":[56,134],"parameters":[57],"used":[58],"in":[59,75,111,124],"how":[63],"they":[64],"alter":[65],"modelled":[70],"It":[72],"optimises":[73],"these":[74],"GP":[78],"tuned":[81],"model":[82],"has":[83,93],"subtle":[84],"but":[85],"important":[86],"differences":[87],"with":[88],"impacts":[94],"on":[95],"understanding":[101],"(inference)":[102],"that":[103],"extracted":[106],"from":[107],"turn":[112],"suggest":[113],"need":[115],"examine":[116],"underlying":[118],"semantics":[119],"resultant":[122],"models":[123],"relation":[125],"scale":[128],"suggested":[131],"parameters.":[135],"A":[136],"number":[137],"areas":[139],"further":[141],"are":[143],"identified.":[144]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
