{"id":"https://openalex.org/W2922300497","doi":"https://doi.org/10.1080/03610918.2019.1586929","title":"Estimation and testing for the integer-valued threshold autoregressive models based on negative binomial thinning","display_name":"Estimation and testing for the integer-valued threshold autoregressive models based on negative binomial thinning","publication_year":2019,"publication_date":"2019-03-14","ids":{"openalex":"https://openalex.org/W2922300497","doi":"https://doi.org/10.1080/03610918.2019.1586929","mag":"2922300497"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1586929","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1586929","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-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/A5115589178","display_name":"Xiaohong Wang","orcid":"https://orcid.org/0009-0004-0323-3077"},"institutions":[{"id":"https://openalex.org/I149240348","display_name":"Jilin Normal University","ror":"https://ror.org/00xtsag93","country_code":"CN","type":"education","lineage":["https://openalex.org/I149240348"]},{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohong Wang","raw_affiliation_strings":["College of Mathematics, Jilin Normal University, Siping, Jilin, China","School of Mathematics, Jilin University, Changchun, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics, Jilin Normal University, Siping, Jilin, China","institution_ids":["https://openalex.org/I149240348"]},{"raw_affiliation_string":"School of Mathematics, Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056125182","display_name":"Dehui Wang","orcid":"https://orcid.org/0000-0002-9185-9034"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dehui Wang","raw_affiliation_strings":["School of Mathematics, Jilin University, Changchun, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074722097","display_name":"Kai Yang","orcid":"https://orcid.org/0000-0002-3038-5293"},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":"CN","type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Yang","raw_affiliation_strings":["School of Mathematics and Statistics, Changchun University of Technology, Changchun, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Changchun University of Technology, Changchun, Jilin, China","institution_ids":["https://openalex.org/I4385474403"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101922256","display_name":"Da Xu","orcid":"https://orcid.org/0000-0002-6159-7109"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Xu","raw_affiliation_strings":["School of Mathematics, Jilin University, Changchun, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074722097"],"corresponding_institution_ids":["https://openalex.org/I4385474403"],"apc_list":null,"apc_paid":null,"fwci":2.0309,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.86830196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"50","issue":"6","first_page":"1622","last_page":"1644"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"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/T10136","display_name":"Statistical Methods and Inference","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overdispersion","display_name":"Overdispersion","score":0.86371910572052},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.7789893746376038},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7233703136444092},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6197792291641235},{"id":"https://openalex.org/keywords/star-model","display_name":"STAR model","score":0.5729619264602661},{"id":"https://openalex.org/keywords/binomial","display_name":"Binomial (polynomial)","score":0.5623964071273804},{"id":"https://openalex.org/keywords/binomial-test","display_name":"Binomial test","score":0.5348562002182007},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5247045755386353},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5150163173675537},{"id":"https://openalex.org/keywords/integer","display_name":"Integer (computer science)","score":0.4801849126815796},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.4478673040866852},{"id":"https://openalex.org/keywords/interval-estimation","display_name":"Interval estimation","score":0.44391587376594543},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.4389662742614746},{"id":"https://openalex.org/keywords/quasi-likelihood","display_name":"Quasi-likelihood","score":0.4156852960586548},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.349479615688324},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.3320960998535156},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.31725233793258667},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2417183220386505},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.1485796570777893},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.07018959522247314}],"concepts":[{"id":"https://openalex.org/C117236510","wikidata":"https://www.wikidata.org/wiki/Q7113620","display_name":"Overdispersion","level":4,"score":0.86371910572052},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.7789893746376038},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7233703136444092},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6197792291641235},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.5729619264602661},{"id":"https://openalex.org/C2781315470","wikidata":"https://www.wikidata.org/wiki/Q193623","display_name":"Binomial (polynomial)","level":2,"score":0.5623964071273804},{"id":"https://openalex.org/C148444598","wikidata":"https://www.wikidata.org/wiki/Q864022","display_name":"Binomial test","level":4,"score":0.5348562002182007},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5247045755386353},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5150163173675537},{"id":"https://openalex.org/C97137487","wikidata":"https://www.wikidata.org/wiki/Q729138","display_name":"Integer (computer science)","level":2,"score":0.4801849126815796},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4478673040866852},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.44391587376594543},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.4389662742614746},{"id":"https://openalex.org/C91025261","wikidata":"https://www.wikidata.org/wiki/Q7269460","display_name":"Quasi-likelihood","level":4,"score":0.4156852960586548},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.349479615688324},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3320960998535156},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.31725233793258667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2417183220386505},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.1485796570777893},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.07018959522247314},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1586929","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1586929","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8399999737739563}],"awards":[{"id":"https://openalex.org/G4022178438","display_name":null,"funder_award_id":"16BTJ020","funder_id":"https://openalex.org/F4320335869","funder_display_name":"National Social Science Fund of China"},{"id":"https://openalex.org/G7614848475","display_name":null,"funder_award_id":"11501241,11571051,11731015,11871028,J1310022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8041962056","display_name":null,"funder_award_id":"20150520053JH,20170101057JC,20180101216JC","funder_id":"https://openalex.org/F4320310121","funder_display_name":"Natural Science Foundation of Jilin Province"}],"funders":[{"id":"https://openalex.org/F4320310121","display_name":"Natural Science Foundation of Jilin Province","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335869","display_name":"National Social Science Fund of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W233732681","https://openalex.org/W1606326889","https://openalex.org/W1930187923","https://openalex.org/W1968781318","https://openalex.org/W1982191138","https://openalex.org/W1982288993","https://openalex.org/W1998237498","https://openalex.org/W2011928446","https://openalex.org/W2032051534","https://openalex.org/W2035623448","https://openalex.org/W2038364295","https://openalex.org/W2043131298","https://openalex.org/W2044045490","https://openalex.org/W2044121999","https://openalex.org/W2045945507","https://openalex.org/W2062541416","https://openalex.org/W2106705814","https://openalex.org/W2116855184","https://openalex.org/W2147545132","https://openalex.org/W2151164623","https://openalex.org/W2151540825","https://openalex.org/W2165098365","https://openalex.org/W2172241436","https://openalex.org/W2235845075","https://openalex.org/W2255141750","https://openalex.org/W2297467798","https://openalex.org/W2323943544","https://openalex.org/W2341516299","https://openalex.org/W2478692615","https://openalex.org/W2560551712","https://openalex.org/W2731278514","https://openalex.org/W2739583473","https://openalex.org/W2739836199","https://openalex.org/W2740463054","https://openalex.org/W2769687664","https://openalex.org/W2963777128","https://openalex.org/W4210688903","https://openalex.org/W4239333055","https://openalex.org/W4248242905","https://openalex.org/W4301048281"],"related_works":["https://openalex.org/W2887034083","https://openalex.org/W2022291863","https://openalex.org/W1973125087","https://openalex.org/W1987173561","https://openalex.org/W2151540825","https://openalex.org/W1978964549","https://openalex.org/W4253136128","https://openalex.org/W2092017416","https://openalex.org/W2114546587","https://openalex.org/W2023970852"],"abstract_inverted_index":{"To":[0],"better":[1],"describe":[2],"the":[3,21,37,40,57,60],"characteristics":[4],"of":[5,8,39,59,75],"time":[6],"series":[7],"counts":[9],"such":[10],"as":[11],"overdispersion":[12],"or":[13],"structural":[14],"change,":[15],"in":[16],"this":[17],"paper,":[18],"we":[19,67],"redefines":[20],"integer-valued":[22],"threshold":[23],"autoregressive":[24],"models":[25],"based":[26],"on":[27],"negative":[28],"binomial":[29],"thinning":[30],"(NBTINAR(1))":[31],"under":[32],"a":[33,69],"weaker":[34],"condition":[35],"that":[36],"expectation":[38],"innovations":[41],"is":[42,62],"finite.":[43],"Parameters\u2019":[44],"point":[45],"estimation":[46,49],"and":[47,72],"interval":[48],"problems":[50],"are":[51],"considered.":[52],"A":[53],"method":[54],"to":[55],"test":[56],"nonlinearity":[58],"data":[61,78],"provided.":[63],"As":[64],"an":[65],"illustration,":[66],"conduct":[68],"simulation":[70],"study":[71],"empirical":[73],"analysis":[74],"Pittsburgh":[76],"crime":[77],"sets.":[79]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}