{"id":"https://openalex.org/W2810878722","doi":"https://doi.org/10.1007/s11222-018-9820-8","title":"Long memory estimation for complex-valued time series","display_name":"Long memory estimation for complex-valued time series","publication_year":2018,"publication_date":"2018-07-04","ids":{"openalex":"https://openalex.org/W2810878722","doi":"https://doi.org/10.1007/s11222-018-9820-8","mag":"2810878722"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-018-9820-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9820-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9820-8.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"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9820-8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067487855","display_name":"Marina I. Knight","orcid":"https://orcid.org/0000-0001-9926-6092"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Marina I. Knight","raw_affiliation_strings":["Department of Mathematics, University of York, Heslington, York, YO10 5DD, UK"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of York, Heslington, York, YO10 5DD, UK","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062068953","display_name":"Matthew A. Nunes","orcid":"https://orcid.org/0000-0002-4719-2690"},"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":"Matthew A. Nunes","raw_affiliation_strings":["Department of Mathematics and Statistics, Fylde College, Lancaster University, Lancaster, LA1 4YF, UK"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Fylde College, Lancaster University, Lancaster, LA1 4YF, UK","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062068953"],"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":4.9793,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.95273093,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"29","issue":"3","first_page":"517","last_page":"536"},"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":0.9984999895095825,"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":0.9984999895095825,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/hurst-exponent","display_name":"Hurst exponent","score":0.863157331943512},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6181962490081787},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5765503644943237},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5702184438705444},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5658017992973328},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5571154952049255},{"id":"https://openalex.org/keywords/detrended-fluctuation-analysis","display_name":"Detrended fluctuation analysis","score":0.49759677052497864},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48859483003616333},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4412814974784851},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42913568019866943},{"id":"https://openalex.org/keywords/complex-system","display_name":"Complex system","score":0.42578941583633423},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3945394456386566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31117191910743713},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.272578626871109},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23705947399139404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19468221068382263}],"concepts":[{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.863157331943512},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6181962490081787},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5765503644943237},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5702184438705444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5658017992973328},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5571154952049255},{"id":"https://openalex.org/C21689155","wikidata":"https://www.wikidata.org/wiki/Q2451452","display_name":"Detrended fluctuation analysis","level":3,"score":0.49759677052497864},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48859483003616333},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4412814974784851},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42913568019866943},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.42578941583633423},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3945394456386566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31117191910743713},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.272578626871109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23705947399139404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19468221068382263},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"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":3,"locations":[{"id":"doi:10.1007/s11222-018-9820-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9820-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9820-8.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":"pmh:oai:eprints.lancs.ac.uk:126078","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.lancs.ac.uk/id/eprint/126078/1/complexHurstr1.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:eprints.whiterose.ac.uk:132566","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-9926-6092>","pdf_url":"https://eprints.whiterose.ac.uk/132566/1/complexHurstr1.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"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"}],"best_oa_location":{"id":"doi:10.1007/s11222-018-9820-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9820-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9820-8.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":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.800000011920929}],"awards":[],"funders":[{"id":"https://openalex.org/F4320311714","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2810878722.pdf","grobid_xml":"https://content.openalex.org/works/W2810878722.grobid-xml"},"referenced_works_count":105,"referenced_works":["https://openalex.org/W142384176","https://openalex.org/W186621202","https://openalex.org/W563452052","https://openalex.org/W639989723","https://openalex.org/W1507807393","https://openalex.org/W1508427692","https://openalex.org/W1594723396","https://openalex.org/W1598517949","https://openalex.org/W1607632979","https://openalex.org/W1755246693","https://openalex.org/W1908845184","https://openalex.org/W1937245514","https://openalex.org/W1968358072","https://openalex.org/W1968798675","https://openalex.org/W1970102186","https://openalex.org/W1974517140","https://openalex.org/W1974581749","https://openalex.org/W1974673435","https://openalex.org/W1979411974","https://openalex.org/W1982176366","https://openalex.org/W1990862516","https://openalex.org/W1992662982","https://openalex.org/W1996387237","https://openalex.org/W2000752159","https://openalex.org/W2007501689","https://openalex.org/W2011294979","https://openalex.org/W2012951355","https://openalex.org/W2016078606","https://openalex.org/W2016639956","https://openalex.org/W2017821362","https://openalex.org/W2018332268","https://openalex.org/W2020743612","https://openalex.org/W2022777787","https://openalex.org/W2023815042","https://openalex.org/W2024638876","https://openalex.org/W2025900077","https://openalex.org/W2030177986","https://openalex.org/W2031753087","https://openalex.org/W2040829107","https://openalex.org/W2041043544","https://openalex.org/W2041310429","https://openalex.org/W2041817790","https://openalex.org/W2047063224","https://openalex.org/W2047627251","https://openalex.org/W2051547395","https://openalex.org/W2052745931","https://openalex.org/W2058087147","https://openalex.org/W2060954056","https://openalex.org/W2066741947","https://openalex.org/W2067180668","https://openalex.org/W2084528906","https://openalex.org/W2084598419","https://openalex.org/W2088272457","https://openalex.org/W2089144299","https://openalex.org/W2090267260","https://openalex.org/W2092416301","https://openalex.org/W2096844050","https://openalex.org/W2098395267","https://openalex.org/W2098918476","https://openalex.org/W2100478220","https://openalex.org/W2102214133","https://openalex.org/W2107473219","https://openalex.org/W2120236826","https://openalex.org/W2120371717","https://openalex.org/W2122675669","https://openalex.org/W2123827510","https://openalex.org/W2129152588","https://openalex.org/W2129270815","https://openalex.org/W2129276048","https://openalex.org/W2142221197","https://openalex.org/W2144602403","https://openalex.org/W2153111581","https://openalex.org/W2159071216","https://openalex.org/W2165773639","https://openalex.org/W2168500104","https://openalex.org/W2169430226","https://openalex.org/W2170262959","https://openalex.org/W2293669764","https://openalex.org/W2294288691","https://openalex.org/W2325530052","https://openalex.org/W2338002795","https://openalex.org/W2340179090","https://openalex.org/W2341760625","https://openalex.org/W2345828563","https://openalex.org/W2394909248","https://openalex.org/W2404595025","https://openalex.org/W2476841360","https://openalex.org/W2510977193","https://openalex.org/W2515059966","https://openalex.org/W2522027325","https://openalex.org/W2572138262","https://openalex.org/W2606907027","https://openalex.org/W2747834867","https://openalex.org/W2891665580","https://openalex.org/W2963702175","https://openalex.org/W2996955947","https://openalex.org/W3005617750","https://openalex.org/W3021380660","https://openalex.org/W3098598356","https://openalex.org/W3100557098","https://openalex.org/W3102362558","https://openalex.org/W3105762472","https://openalex.org/W3180436685","https://openalex.org/W4211251910","https://openalex.org/W4249060944"],"related_works":["https://openalex.org/W2031055538","https://openalex.org/W4295222450","https://openalex.org/W2469338325","https://openalex.org/W2949563423","https://openalex.org/W1235680255","https://openalex.org/W2391138490","https://openalex.org/W2560106835","https://openalex.org/W3005617750","https://openalex.org/W2810878722","https://openalex.org/W2519828820"],"abstract_inverted_index":{"Long":[0],"memory":[1],"has":[2],"been":[3],"observed":[4],"for":[5,20,28,99],"time":[6,53],"series":[7,54],"across":[8,139],"a":[9,51,82,93,117,140],"multitude":[10],"of":[11,17,33,37,84,116,132,142,159],"fields,":[12],"and":[13,31,58,63,77,145,147,166],"the":[14,23,29,130,133,160,164],"accurate":[15],"estimation":[16,97,135],"such":[18],"dependence,":[19],"example":[21],"via":[22],"Hurst":[24,88,95],"exponent,":[25],"is":[26,74,109],"crucial":[27],"modelling":[30,190],"prediction":[32],"many":[34],"dynamic":[35],"systems":[36],"interest.":[38],"Many":[39],"physical":[40],"processes":[41],"(such":[42],"as":[43,50],"wind":[44,152],"data)":[45],"are":[46],"more":[47],"naturally":[48],"expressed":[49],"complex-valued":[52,100,119,172],"to":[55],"represent":[56],"magnitude":[57],"phase":[59],"information":[60],"(wind":[61],"speed":[62],"direction).":[64],"With":[65],"data":[66,102],"collection":[67],"ubiquitously":[68],"unreliable,":[69],"irregular":[70],"sampling":[71,143],"or":[72,191],"missingness":[73],"also":[75,123],"commonplace":[76],"can":[78,174],"cause":[79],"bias":[80],"in":[81,125,170],"range":[83,141],"analysis":[85,185],"tasks,":[86],"including":[87],"estimation.":[89,200],"This":[90],"article":[91],"proposes":[92],"new":[94,118],"exponent":[96],"technique":[98],"persistent":[101,149],"sampled":[103],"with":[104,195],"potential":[105],"irregularity.":[106],"Our":[107],"approach":[108],"justified":[110],"through":[111,137],"establishing":[112],"attractive":[113],"theoretical":[114],"properties":[115],"wavelet":[120],"lifting":[121],"transform,":[122],"introduced":[124],"this":[126],"paper.":[127],"We":[128],"demonstrate":[129],"accuracy":[131],"proposed":[134],"method":[136,155],"simulations":[138],"scenarios":[144],"complex-":[146],"real-valued":[148,182,199],"processes.":[150],"For":[151],"data,":[153,168],"our":[154,171],"highlights":[156],"that":[157],"inclusion":[158],"intrinsic":[161],"correlations":[162],"between":[163],"real":[165],"imaginary":[167],"inherent":[169],"approach,":[173],"produce":[175],"different":[176],"persistence":[177],"estimates":[178],"than":[179],"when":[180],"using":[181],"analysis.":[183],"Such":[184],"could":[186],"then":[187],"support":[188],"alternative":[189],"policy":[192],"decisions":[193],"compared":[194],"conclusions":[196],"based":[197],"on":[198]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
