{"id":"https://openalex.org/W2992929501","doi":null,"title":"Geographichal Weighted Regression and Mix Geographichal Weighted Regression","display_name":"Geographichal Weighted Regression and Mix Geographichal Weighted Regression","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2992929501","mag":"2992929501"},"language":"en","primary_location":{"id":"mag:2992929501","doi":null,"is_oa":true,"landing_page_url":"http://article.sapub.org/10.5923.j.statistics.20150501.01.html","pdf_url":null,"source":{"id":"https://openalex.org/S2764685691","display_name":"International journal of statistics and applications","issn_l":"2168-5193","issn":["2168-5193","2168-5215"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["anvur-scientific"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International journal of statistics and applications","raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://article.sapub.org/10.5923.j.statistics.20150501.01.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029699077","display_name":"Fernando Pongoh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fernando Pongoh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058427120","display_name":"I Made Sumertajaya","orcid":"https://orcid.org/0000-0002-2682-7941","observed_orcids":["https://orcid.org/0000-0002-2682-7941"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"I Made Sumertajaya","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2682-7941","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056440391","display_name":"Muhammad Nur Aidi","orcid":"https://orcid.org/0000-0002-9463-9141","observed_orcids":["https://orcid.org/0000-0002-9463-9141","https://orcid.org/0000-0001-7971-3123"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muhammad Nur Aidi","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9463-9141","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7221,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80619874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"5","issue":"1","first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9771000146865845,"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":0.9771000146865845,"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/T14509","display_name":"demographic modeling and climate adaptation","score":0.008500000461935997,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10446","display_name":"Income, Poverty, and Inequality","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/poverty","display_name":"poverty","score":0.9470000267028809},{"id":"https://openalex.org/keywords/geographically-weighted-regression","display_name":"geographically weighted regression","score":0.7089999914169312},{"id":"https://openalex.org/keywords/spatial-heterogeneity","display_name":"spatial heterogeneity","score":0.6909999847412109},{"id":"https://openalex.org/keywords/household-characteristics","display_name":"household characteristics","score":0.5910000205039978}],"concepts":[{"id":"https://openalex.org/C2910321205","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geographically Weighted Regression","level":2,"score":0.6926001310348511},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6427366733551025},{"id":"https://openalex.org/C189326681","wikidata":"https://www.wikidata.org/wiki/Q10294","display_name":"Poverty","level":2,"score":0.6314584612846375},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5889803171157837},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5599372982978821},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5427238941192627},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5325129628181458},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5159547924995422},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.5090898871421814},{"id":"https://openalex.org/C100243477","wikidata":"https://www.wikidata.org/wiki/Q12002092","display_name":"Welfare","level":2,"score":0.49511852860450745},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4607565999031067},{"id":"https://openalex.org/C45355965","wikidata":"https://www.wikidata.org/wiki/Q1643441","display_name":"Socioeconomics","level":1,"score":0.3284032344818115},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.16949796676635742},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.1083182692527771},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2992929501","doi":null,"is_oa":true,"landing_page_url":"http://article.sapub.org/10.5923.j.statistics.20150501.01.html","pdf_url":null,"source":{"id":"https://openalex.org/S2764685691","display_name":"International journal of statistics and applications","issn_l":"2168-5193","issn":["2168-5193","2168-5215"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["anvur-scientific"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International journal of statistics and applications","raw_type":null}],"best_oa_location":{"id":"mag:2992929501","doi":null,"is_oa":true,"landing_page_url":"http://article.sapub.org/10.5923.j.statistics.20150501.01.html","pdf_url":null,"source":{"id":"https://openalex.org/S2764685691","display_name":"International journal of statistics and applications","issn_l":"2168-5193","issn":["2168-5193","2168-5215"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["anvur-scientific"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International journal of statistics and applications","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.8928999900817871},{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7578999996185303}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2751549182"],"related_works":["https://openalex.org/W7171322778","https://openalex.org/W2740080660","https://openalex.org/W4293757456","https://openalex.org/W1548954634","https://openalex.org/W3214986263","https://openalex.org/W2116439365","https://openalex.org/W4401636471","https://openalex.org/W2902448481","https://openalex.org/W1972330578","https://openalex.org/W2790150421"],"abstract_inverted_index":{"Poverty":[0],"is":[1,79,134],"a":[2,80],"fundamental":[3],"problem":[4],"that":[5,20],"existed":[6],"and":[7,67,113,160,162,170],"still":[8],"occurs":[9],"in":[10,26,44,49,83,147],"Indonesia.":[11],"This":[12],"analysis":[13,77],"was":[14],"conducted":[15],"to":[16,38,85,138],"describe":[17],"the":[18,22,102,119,135,140,143,155,163],"factors":[19],"influence":[21,36,141],"welfare":[23,145],"low":[24,144],"status":[25,40,146],"sub-districts":[27,148],"of":[28,87,94,142,149,158,165],"North":[29,150],"Sulawesi":[30,151],"Province.":[31],"Global":[32,168],"regression":[33,76,107],"has":[34,96,110,124,154],"obtained":[35],"variables":[37],"poverty":[39],"are":[41],"woman":[42],"leader":[43],"household":[45,63,68],"(X1),":[46],"Child":[47],"not":[48],"formal":[50],"education":[51],"(X2),":[52],"physical":[53],"defect":[54],"(X3),":[55],"chronic":[56],"desease":[57],"victim":[58],"(X5),":[59],"self-owned":[60],"house":[61],"(X6),":[62],"using":[64,69],"electricity":[65],"(X8)":[66],"its":[70],"own":[71],"toilet":[72],"(X10).":[73],"Geographical":[74,105],"weighted":[75,106],"(GWR)":[78],"locally":[81],"model,":[82],"order":[84],"estimates":[86],"parameters":[88],"at":[89,100,129],"each":[90,101,130],"location.":[91,103,131],"The":[92],"result":[93],"GWR":[95,132],"different":[97,126],"parameter":[98,127],"estimation":[99,128],"Mix":[104],"model":[108,122,137],"(MGWR)":[109],"combined":[111],"local":[112],"global":[114],"parameters.":[115],"As":[116],"well":[117],"as":[118],"GWR,":[120],"MGWR":[121],"results":[123],"give":[125],"Model":[133],"best":[136],"explain":[139],"Province":[152],"which":[153],"smallest":[156],"value":[157],"MSE":[159],"AIC":[161],"largest":[164],"R2":[166],"between":[167],"Regression":[169],"MGWR.":[171]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2019-12-13T00:00:00"}