{"id":"https://openalex.org/W2588239216","doi":"https://doi.org/10.1007/s11222-017-9731-0","title":"Long memory and changepoint models: a spectral classification procedure","display_name":"Long memory and changepoint models: a spectral classification procedure","publication_year":2017,"publication_date":"2017-02-13","ids":{"openalex":"https://openalex.org/W2588239216","doi":"https://doi.org/10.1007/s11222-017-9731-0","mag":"2588239216","pmid":"https://pubmed.ncbi.nlm.nih.gov/31997855"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-017-9731-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-017-9731-0","pdf_url":"https://link.springer.com/content/pdf/10.1007%2Fs11222-017-9731-0.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007%2Fs11222-017-9731-0.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103019484","display_name":"Ben Norwood","orcid":"https://orcid.org/0000-0003-1125-2951"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ben Norwood","raw_affiliation_strings":["Department of Mathematics and Statistics, Lancaster University, LA1 4YF Lancaster, UK","Department of Mathematics and Statistics, Lancaster University, LA1 4YF, Lancaster, UK"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Lancaster University, LA1 4YF Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Department of Mathematics and Statistics, Lancaster University, LA1 4YF, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075851671","display_name":"Rebecca Killick","orcid":"https://orcid.org/0000-0003-0583-3960"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rebecca Killick","raw_affiliation_strings":["Department of Mathematics and Statistics, Lancaster University, LA1 4YF Lancaster, UK","Department of Mathematics and Statistics, Lancaster University, LA1 4YF, Lancaster, UK"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Lancaster University, LA1 4YF Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Department of Mathematics and Statistics, Lancaster University, LA1 4YF, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103019484"],"corresponding_institution_ids":["https://openalex.org/I67415387"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":6.6073,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.96446071,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"28","issue":"2","first_page":"291","last_page":"302"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9983000159263611,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9983000159263611,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.989799976348877,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.6645860075950623},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6593976616859436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6016273498535156},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5336143970489502},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4537903666496277},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4320620000362396},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4212225675582886},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.41617920994758606},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4160200357437134},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3734655976295471},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35734015703201294},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34254127740859985},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31898733973503113},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20544064044952393}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6645860075950623},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6593976616859436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6016273498535156},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5336143970489502},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4537903666496277},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4320620000362396},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4212225675582886},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.41617920994758606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4160200357437134},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3734655976295471},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35734015703201294},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34254127740859985},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31898733973503113},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20544064044952393},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s11222-017-9731-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-017-9731-0","pdf_url":"https://link.springer.com/content/pdf/10.1007%2Fs11222-017-9731-0.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmid:31997855","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31997855","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and computing","raw_type":null},{"id":"pmh:oai:eprints.lancs.ac.uk:84670","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.lancs.ac.uk/id/eprint/84670/1/Paper.pdf","source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:escholarship.org:ark:/13030/qt2q63442q","is_oa":true,"landing_page_url":"https://escholarship.org/uc/item/2q63442q","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Statistics and Computing, vol 28, iss 2","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5927087","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6956897","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s11222-017-9731-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-017-9731-0","pdf_url":"https://link.springer.com/content/pdf/10.1007%2Fs11222-017-9731-0.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6399999856948853}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334630","display_name":"Economic and Social Research Council","ror":"https://ror.org/03n0ht308"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2588239216.pdf","grobid_xml":"https://content.openalex.org/works/W2588239216.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1545954990","https://openalex.org/W1584186729","https://openalex.org/W1764566655","https://openalex.org/W1900456343","https://openalex.org/W1975441639","https://openalex.org/W1975684011","https://openalex.org/W1977176085","https://openalex.org/W1982121092","https://openalex.org/W1997029252","https://openalex.org/W2000453393","https://openalex.org/W2041402087","https://openalex.org/W2049057506","https://openalex.org/W2059163482","https://openalex.org/W2062024414","https://openalex.org/W2071144963","https://openalex.org/W2080284552","https://openalex.org/W2116512828","https://openalex.org/W2124533898","https://openalex.org/W2132090039","https://openalex.org/W2141319874","https://openalex.org/W2150531337","https://openalex.org/W2154486377","https://openalex.org/W2182075928","https://openalex.org/W2773620921","https://openalex.org/W3105649530","https://openalex.org/W3124955081","https://openalex.org/W4255272544"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4205958290","https://openalex.org/W2541950815"],"abstract_inverted_index":{"Time":[0],"series":[1,25,36],"within":[2,33,56],"fields":[3],"such":[4,54],"as":[5,55],"finance":[6],"and":[7,135,156],"economics":[8],"are":[9,121],"often":[10],"modelled":[11],"using":[12,92],"long":[13],"memory":[14,116],"processes.":[15],"Alternative":[16],"studies":[17],"on":[18,151],"the":[19,34,38,93,100,111,142],"same":[20],"data":[21,39],"can":[22],"suggest":[23],"that":[24,84,141],"may":[26],"actually":[27],"contain":[28],"a":[29,89,106,124,152],"'changepoint'":[30],"(a":[31],"point":[32],"time":[35],"where":[37],"generating":[40],"process":[41],"has":[42],"changed).":[43],"These":[44],"models":[45,127,155],"have":[46,50],"been":[47],"shown":[48],"to":[49,64,75,109,132],"elements":[51],"of":[52,126,154],"similarity,":[53],"their":[57],"spectrum.":[58],"Without":[59],"prior":[60],"knowledge":[61],"this":[62,86,97],"leads":[63],"an":[65,130,146],"ambiguity":[66],"between":[67],"these":[68],"two":[69],"models,":[70],"meaning":[71],"it":[72],"is":[73,79],"difficult":[74],"assess":[76],"which":[77],"model":[78,114],"most":[80,112],"appropriate.":[81],"We":[82],"demonstrate":[83],"considering":[85],"problem":[87],"in":[88],"time-varying":[90,94],"environment":[91],"spectrum":[95],"removes":[96],"ambiguity.":[98],"Using":[99],"wavelet":[101],"spectrum,":[102],"we":[103],"then":[104],"use":[105],"classification":[107,144],"approach":[108,150],"determine":[110],"appropriate":[113],"(long":[115],"or":[117],"changepoint).":[118],"Simulation":[119],"results":[120,139],"presented":[122],"across":[123,159],"number":[125,153],"followed":[128],"by":[129],"application":[131],"stock":[133],"cross-correlations":[134],"US":[136],"inflation.":[137],"The":[138],"indicate":[140],"proposed":[143],"outperforms":[145],"existing":[147],"hypothesis":[148],"testing":[149],"performs":[157],"comparatively":[158],"others.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
