{"id":"https://openalex.org/W2130409740","doi":"https://doi.org/10.1109/fuzzy.2011.6007470","title":"The interval autoregressive time series model","display_name":"The interval autoregressive time series model","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2130409740","doi":"https://doi.org/10.1109/fuzzy.2011.6007470","mag":"2130409740"},"language":"en","primary_location":{"id":"doi:10.1109/fuzzy.2011.6007470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2011.6007470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)","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/A5100333850","display_name":"Xun Wang","orcid":"https://orcid.org/0000-0002-1156-3840"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xun Wang","raw_affiliation_strings":["Department of Applied Mathematics, Beijing University of Technology, Beijing, China","Department of Applied Mathematics, Beijing University of Technology, Beijing, China 100124#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]},{"raw_affiliation_string":"Department of Applied Mathematics, Beijing University of Technology, Beijing, China 100124#TAB#","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060571396","display_name":"Shoumei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoumei Li","raw_affiliation_strings":["Department of Applied Mathematics, Beijing University of Technology, Beijing, China","Department of Applied Mathematics, Beijing University of Technology, Beijing, China 100124#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]},{"raw_affiliation_string":"Department of Applied Mathematics, Beijing University of Technology, Beijing, China 100124#TAB#","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100333850"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":1.6389,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.85392347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2528","last_page":"2533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9706000089645386,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.7629795074462891},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7465896010398865},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6638436913490295},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6264756917953491},{"id":"https://openalex.org/keywords/prediction-interval","display_name":"Prediction interval","score":0.6206458806991577},{"id":"https://openalex.org/keywords/interval-estimation","display_name":"Interval estimation","score":0.5568429827690125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.540999174118042},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.4632602334022522},{"id":"https://openalex.org/keywords/interval-data","display_name":"Interval data","score":0.43642663955688477},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.42487287521362305},{"id":"https://openalex.org/keywords/star-model","display_name":"STAR model","score":0.41215115785598755},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3677850365638733},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34174489974975586},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3229103684425354},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.24994540214538574},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21494010090827942}],"concepts":[{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.7629795074462891},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7465896010398865},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6638436913490295},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6264756917953491},{"id":"https://openalex.org/C103402496","wikidata":"https://www.wikidata.org/wiki/Q1106171","display_name":"Prediction interval","level":2,"score":0.6206458806991577},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.5568429827690125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.540999174118042},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.4632602334022522},{"id":"https://openalex.org/C2983220686","wikidata":"https://www.wikidata.org/wiki/Q951437","display_name":"Interval data","level":3,"score":0.43642663955688477},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.42487287521362305},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.41215115785598755},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3677850365638733},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34174489974975586},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3229103684425354},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.24994540214538574},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21494010090827942},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzzy.2011.6007470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2011.6007470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W53521131","https://openalex.org/W63818593","https://openalex.org/W1528966910","https://openalex.org/W1695350145","https://openalex.org/W2016415759","https://openalex.org/W2021244475","https://openalex.org/W2024880014","https://openalex.org/W2036704699","https://openalex.org/W2051783828","https://openalex.org/W2058815839","https://openalex.org/W2075234505","https://openalex.org/W2075646905","https://openalex.org/W2075848956","https://openalex.org/W2081004173","https://openalex.org/W2090049808","https://openalex.org/W2123536266","https://openalex.org/W2124116645","https://openalex.org/W2131318422","https://openalex.org/W2131453387","https://openalex.org/W2133442842","https://openalex.org/W2134752891","https://openalex.org/W2136691316","https://openalex.org/W2145705229","https://openalex.org/W2162129402","https://openalex.org/W2168577773","https://openalex.org/W2171816001","https://openalex.org/W2268508373","https://openalex.org/W2798056406","https://openalex.org/W4285719527","https://openalex.org/W6679574406","https://openalex.org/W6693948062"],"related_works":["https://openalex.org/W2041819240","https://openalex.org/W2045103335","https://openalex.org/W199725827","https://openalex.org/W4248896451","https://openalex.org/W1484537345","https://openalex.org/W4249363612","https://openalex.org/W2228548008","https://openalex.org/W81705085","https://openalex.org/W2126250021","https://openalex.org/W2063870691"],"abstract_inverted_index":{"This":[0,103],"paper":[1],"mainly":[2],"suggests":[3],"a":[4],"new":[5],"type":[6],"of":[7,44,49,68],"interval":[8,11,23,36,50,78],"time":[9,24,37,51],"series:":[10],"autoregressive":[12],"(IAR)":[13],"model.":[14],"Firstly":[15],"we":[16,19,28,40,55,81],"state":[17],"why":[18],"should":[20],"introduce":[21,41],"the":[22,66,74,83,113],"series":[25],"models.":[26],"Then":[27],"give":[29,82],"necessary":[30],"definitions":[31],"about":[32],"random":[33],"intervals":[34],"and":[35,59,86,115],"series.":[38,52],"Thirdly,":[39],"some":[42],"methods":[43,67],"efficiency":[45],"evaluation":[46,75],"for":[47,77,108],"forecasting":[48,60,76],"And":[53],"then":[54],"discuss":[56],"parameter":[57,69],"estimation":[58,70],"in":[61,64],"IAR":[62],"model,":[63],"which":[65,96],"are":[71],"based":[72,119],"on":[73,120],"data.":[79],"Furthermore,":[80],"simulation":[84],"results":[85],"apply":[87],"it":[88,106],"to":[89,98,111],"real":[90],"data":[91],"from":[92],"Shanghai":[93],"Stock":[94],"Index,":[95],"is":[97],"illustrate":[99],"our":[100],"modeling":[101],"methodology.":[102],"model":[104],"makes":[105],"possible":[107,117],"decision":[109],"makers":[110],"forecast":[112],"best":[114],"worst":[116],"situations":[118],"interval-valued":[121],"observations.":[122]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}