{"id":"https://openalex.org/W2982991612","doi":"https://doi.org/10.1109/igarss.2019.8899281","title":"Two Stage Estimation Procedure for Spatial Regression Models and Model Selection","display_name":"Two Stage Estimation Procedure for Spatial Regression Models and Model Selection","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2982991612","doi":"https://doi.org/10.1109/igarss.2019.8899281","mag":"2982991612"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5037560668","display_name":"Shojiro Tanaka","orcid":"https://orcid.org/0000-0003-0846-1912"},"institutions":[{"id":"https://openalex.org/I183792356","display_name":"Hiroshima University of Economics","ror":"https://ror.org/027b58k10","country_code":"JP","type":"education","lineage":["https://openalex.org/I183792356"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shojiro Tanaka","raw_affiliation_strings":["Faculty of Economics, Hiroshima University of Economics, Hiroshima, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Economics, Hiroshima University of Economics, Hiroshima, Japan","institution_ids":["https://openalex.org/I183792356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070567505","display_name":"Ryuei Nishii","orcid":"https://orcid.org/0000-0001-8109-6638"},"institutions":[{"id":"https://openalex.org/I43777268","display_name":"Nagasaki University","ror":"https://ror.org/058h74p94","country_code":"JP","type":"education","lineage":["https://openalex.org/I43777268"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuei Nishii","raw_affiliation_strings":["Office for Establishment of an Information-related School, Nagasaki University, Nagasaki, Japan"],"affiliations":[{"raw_affiliation_string":"Office for Establishment of an Information-related School, Nagasaki University, Nagasaki, Japan","institution_ids":["https://openalex.org/I43777268"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064835307","display_name":"Gigih Fitrianto","orcid":"https://orcid.org/0000-0003-2168-7721"},"institutions":[{"id":"https://openalex.org/I183792356","display_name":"Hiroshima University of Economics","ror":"https://ror.org/027b58k10","country_code":"JP","type":"education","lineage":["https://openalex.org/I183792356"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gigih Fitrianto","raw_affiliation_strings":["Graduate School of Economics, Hiroshima University of Economics, Hiroshima, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Economics, Hiroshima University of Economics, Hiroshima, Japan","institution_ids":["https://openalex.org/I183792356"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037560668"],"corresponding_institution_ids":["https://openalex.org/I183792356"],"apc_list":null,"apc_paid":null,"fwci":0.1118,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47645887,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"342","issue":null,"first_page":"1919","last_page":"1922"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9980000257492065,"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":0.9980000257492065,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9944999814033508,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6375662088394165},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5769575238227844},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5756607055664062},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5372374653816223},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5054214000701904},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4830520749092102},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.47165265679359436},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.46716582775115967},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4523731470108032},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.43086445331573486},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4198344945907593},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3961934447288513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31938502192497253},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31173086166381836},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2566109299659729},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06856146454811096}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6375662088394165},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5769575238227844},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5756607055664062},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5372374653816223},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5054214000701904},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4830520749092102},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.47165265679359436},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.46716582775115967},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4523731470108032},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.43086445331573486},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4198344945907593},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3961934447288513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31938502192497253},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31173086166381836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2566109299659729},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06856146454811096},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8899281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1527710572","https://openalex.org/W1947647518","https://openalex.org/W1981213426","https://openalex.org/W1997034892","https://openalex.org/W2033494869","https://openalex.org/W2043649762","https://openalex.org/W2064405084","https://openalex.org/W2065806350","https://openalex.org/W2102806083","https://openalex.org/W2113426089","https://openalex.org/W2120640629","https://openalex.org/W6661476816"],"related_works":["https://openalex.org/W2067317451","https://openalex.org/W2154771632","https://openalex.org/W4211085505","https://openalex.org/W4293088233","https://openalex.org/W3122478268","https://openalex.org/W2084758217","https://openalex.org/W408804804","https://openalex.org/W4231021675","https://openalex.org/W3086365953","https://openalex.org/W4226072953"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,41,52],"two":[6],"stage":[7],"procedure":[8,18],"to":[9,85,97,104],"estimate":[10],"regression":[11],"parameters":[12],"including":[13],"spatial":[14],"dependency.":[15],"The":[16],"proposed":[17,76],"without":[19],"inversion":[20,39],"task":[21],"is":[22],"carried":[23],"out":[24],"very":[25],"fast":[26],"with":[27,71],"small":[28],"memory.":[29],"For":[30],"the":[31,34,79],"model":[32],"estimation,":[33],"neighbor":[35],"effect":[36],"needs":[37],"an":[38],"of":[40,44,82,114],"large":[42],"matrix":[43],"size":[45],"n":[46,48,50],"\u00d7":[47],"where":[49],"denotes":[51],"sample":[53],"size,":[54],"which":[55,108],"requires":[56],"exhaustive":[57],"calculations":[58],"especially":[59],"in":[60,69,100,111],"geosciences.":[61],"It":[62],"has":[63],"been":[64],"attested":[65],"thus":[66],"far":[67],"that":[68],"comparison":[70],"maximum":[72],"likelihood":[73],"estimation(MLE),":[74],"our":[75],"method":[77],"produced":[78],"same":[80],"trend":[81],"relative":[83],"appropriateness":[84],"real":[86],"data":[87],"by":[88],"using":[89],"BIC":[90],"and":[91],"AIC.":[92],"That":[93],"brings":[94],"novel":[95],"possibility":[96],"replace":[98],"MLE":[99],"drastically":[101],"shorter":[102],"time":[103],"avoid":[105],"elaborative":[106],"effort":[107],"sometimes":[109],"results":[110,113],"eratic":[112],"local":[115],"optimization":[116],"also.":[117]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}