{"id":"https://openalex.org/W2080301044","doi":"https://doi.org/10.1080/03610918.2014.1002616","title":"Testing a linear ARMA model against threshold-ARMA models: A Bayesian approach","display_name":"Testing a linear ARMA model against threshold-ARMA models: A Bayesian approach","publication_year":2015,"publication_date":"2015-03-25","ids":{"openalex":"https://openalex.org/W2080301044","doi":"https://doi.org/10.1080/03610918.2014.1002616","mag":"2080301044"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2014.1002616","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2014.1002616","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/A5011930940","display_name":"Rubing Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rubing Liang","raw_affiliation_strings":["College of Science, South China Agricultural University, Guangzhou, P. R. China"],"affiliations":[{"raw_affiliation_string":"College of Science, South China Agricultural University, Guangzhou, P. R. China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069882641","display_name":"Qiang Xia","orcid":"https://orcid.org/0000-0003-2477-1742"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Xia","raw_affiliation_strings":["College of Science, South China Agricultural University, Guangzhou, P. R. China"],"affiliations":[{"raw_affiliation_string":"College of Science, South China Agricultural University, Guangzhou, P. R. China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080280215","display_name":"Jiazhu Pan","orcid":"https://orcid.org/0000-0001-7346-2052"},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jiazhu Pan","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103804579","display_name":"Jinshan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinshan Liu","raw_affiliation_strings":["College of Science, South China Agricultural University, Guangzhou, P. R. China"],"affiliations":[{"raw_affiliation_string":"College of Science, South China Agricultural University, Guangzhou, P. R. China","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069882641"],"corresponding_institution_ids":["https://openalex.org/I101479585"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.06857396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"46","issue":"2","first_page":"1302","last_page":"1317"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9925000071525574,"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"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9925000071525574,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9861999750137329,"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/T10007","display_name":"Monetary Policy and Economic Impact","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2000","display_name":"General Economics, Econometrics and 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"}}],"keywords":[{"id":"https://openalex.org/keywords/akaike-information-criterion","display_name":"Akaike information criterion","score":0.8421794176101685},{"id":"https://openalex.org/keywords/bayesian-information-criterion","display_name":"Bayesian information criterion","score":0.8173849582672119},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6938356757164001},{"id":"https://openalex.org/keywords/reversible-jump-markov-chain-monte-carlo","display_name":"Reversible-jump Markov chain Monte Carlo","score":0.6706489324569702},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.6240241527557373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6212120056152344},{"id":"https://openalex.org/keywords/threshold-model","display_name":"Threshold model","score":0.6028954982757568},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.5972890853881836},{"id":"https://openalex.org/keywords/star-model","display_name":"STAR model","score":0.5423524975776672},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.532896876335144},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5206505656242371},{"id":"https://openalex.org/keywords/information-criteria","display_name":"Information Criteria","score":0.46248894929885864},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.4555749297142029},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.45454806089401245},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.43082869052886963},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38533446192741394},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.36750680208206177},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3572201728820801},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.30935391783714294},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.1259983479976654}],"concepts":[{"id":"https://openalex.org/C126674687","wikidata":"https://www.wikidata.org/wiki/Q1662573","display_name":"Akaike information criterion","level":2,"score":0.8421794176101685},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.8173849582672119},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6938356757164001},{"id":"https://openalex.org/C2780591659","wikidata":"https://www.wikidata.org/wiki/Q17083869","display_name":"Reversible-jump Markov chain Monte Carlo","level":4,"score":0.6706489324569702},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.6240241527557373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6212120056152344},{"id":"https://openalex.org/C202632270","wikidata":"https://www.wikidata.org/wiki/Q7798106","display_name":"Threshold model","level":2,"score":0.6028954982757568},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.5972890853881836},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.5423524975776672},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.532896876335144},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5206505656242371},{"id":"https://openalex.org/C2776709221","wikidata":"https://www.wikidata.org/wiki/Q6031040","display_name":"Information Criteria","level":3,"score":0.46248894929885864},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.4555749297142029},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.45454806089401245},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.43082869052886963},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38533446192741394},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.36750680208206177},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3572201728820801},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.30935391783714294},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.1259983479976654}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/03610918.2014.1002616","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2014.1002616","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"},{"id":"pmh:oai:strathprints.strath.ac.uk:56444","is_oa":false,"landing_page_url":"https://strathprints.strath.ac.uk/view/author/601259.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306402226","display_name":"Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I181647926","host_organization_name":"University of Strathclyde","host_organization_lineage":["https://openalex.org/I181647926"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1556794661","https://openalex.org/W1581264736","https://openalex.org/W1590093017","https://openalex.org/W1606326889","https://openalex.org/W1715272460","https://openalex.org/W1930187923","https://openalex.org/W1984276497","https://openalex.org/W1992397662","https://openalex.org/W1997245915","https://openalex.org/W2007069447","https://openalex.org/W2009605255","https://openalex.org/W2018419811","https://openalex.org/W2018967289","https://openalex.org/W2019541458","https://openalex.org/W2020999234","https://openalex.org/W2056760934","https://openalex.org/W2062708515","https://openalex.org/W2072208595","https://openalex.org/W2087618469","https://openalex.org/W2090862710","https://openalex.org/W2098382481","https://openalex.org/W2106706098","https://openalex.org/W2108207895","https://openalex.org/W2134752891","https://openalex.org/W2138309709","https://openalex.org/W2142635246","https://openalex.org/W2163738067","https://openalex.org/W2242062224","https://openalex.org/W3102100758","https://openalex.org/W4256195327","https://openalex.org/W4362597616","https://openalex.org/W4388215482"],"related_works":["https://openalex.org/W2607006239","https://openalex.org/W2114625140","https://openalex.org/W3187368641","https://openalex.org/W1833443108","https://openalex.org/W2608232002","https://openalex.org/W2009591042","https://openalex.org/W1578405420","https://openalex.org/W2142258617","https://openalex.org/W1496524204","https://openalex.org/W2080301044"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,32,100,115],"Bayesian":[3,85],"approach":[4],"to":[5,54],"test":[6],"linear":[7],"autoregressive":[8,14],"moving-average":[9,15],"(ARMA)":[10],"models":[11,70,94],"against":[12],"threshold":[13,28,72],"(TARMA)":[16],"models.":[17,122],"First,":[18],"the":[19,27,56,89],"marginal":[20],"posterior":[21,57],"densities":[22],"of":[23,31,68],"all":[24],"parameters,":[25],"including":[26],"and":[29,61,79,99,118],"delay,":[30],"TARMA":[33,62,69,93,116,121],"model":[34,117],"are":[35],"obtained":[36],"by":[37],"using":[38],"Gibbs":[39],"sampler":[40],"with":[41],"Metropolis\u2013Hastings":[42],"algorithm.":[43],"Second,":[44],"reversible-jump":[45],"Markov":[46],"chain":[47],"Monte":[48],"Carlo":[49],"(RJMCMC)":[50],"method":[51,107],"is":[52,95],"adopted":[53],"calculate":[55],"probabilities":[58],"for":[59,91,110,119],"ARMA":[60,113],"models:":[63],"Posterior":[64],"evidence":[65],"in":[66],"favor":[67],"indicates":[71],"nonlinearity.":[73],"Finally,":[74],"based":[75],"on":[76],"RJMCMC":[77],"scheme":[78],"Akaike":[80],"information":[81,86],"criterion":[82,87],"(AIC)":[83],"or":[84],"(BIC),":[88],"procedure":[90],"modeling":[92],"exploited.":[96],"Simulation":[97],"experiments":[98],"real":[101],"data":[102],"example":[103],"show":[104],"that":[105],"our":[106],"works":[108],"well":[109],"distinguishing":[111],"an":[112],"from":[114],"building":[120]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
