{"id":"https://openalex.org/W7225794168","doi":"https://doi.org/10.1177/15741699261508760","title":"Refurbished data-driven selection of X-11 seasonal filters","display_name":"Refurbished data-driven selection of X-11 seasonal filters","publication_year":2026,"publication_date":"2026-11-11","ids":{"openalex":"https://openalex.org/W7225794168","doi":"https://doi.org/10.1177/15741699261508760"},"language":"en","primary_location":{"id":"doi:10.1177/15741699261508760","doi":"https://doi.org/10.1177/15741699261508760","is_oa":false,"landing_page_url":"https://doi.org/10.1177/15741699261508760","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-c","anvur-scientific","cwts-core","jufo-1","poland-40","russia-white-list-3"],"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5064844027","display_name":"Karsten Webel","orcid":"https://orcid.org/0000-0001-5538-5428","observed_orcids":["https://orcid.org/0000-0001-5538-5428"]},"institutions":[{"id":"https://openalex.org/I74623043","display_name":"Deutsche Bundesbank","ror":"https://ror.org/03jvfq589","country_code":"DE","type":"other","lineage":["https://openalex.org/I74623043"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Karsten Webel","raw_affiliation_strings":["Deutsche Bundesbank, Directorate General Data & Statistics and Research Centre, Frankfurt am Main, Germany"],"raw_orcid":"https://orcid.org/0000-0001-5538-5428","affiliations":[{"raw_affiliation_string":"Deutsche Bundesbank, Directorate General Data & Statistics and Research Centre, Frankfurt am Main, Germany","institution_ids":["https://openalex.org/I74623043"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5064844027"],"corresponding_institution_ids":["https://openalex.org/I74623043"],"apc_list":{"value":4150,"currency":"USD","value_usd":4150},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.7943999767303467,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.7943999767303467,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.13279999792575836,"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/T13487","display_name":"Statistical and numerical algorithms","score":0.03669999912381172,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C169446498","wikidata":"https://www.wikidata.org/wiki/Q622893","display_name":"Seasonal adjustment","level":3,"score":0.7879999876022339},{"id":"https://openalex.org/C125403950","wikidata":"https://www.wikidata.org/wiki/Q2111082","display_name":"Seasonality","level":2,"score":0.7706000208854675},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6919999718666077},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.6146000027656555},{"id":"https://openalex.org/C63382987","wikidata":"https://www.wikidata.org/wiki/Q455204","display_name":"Hodrick\u2013Prescott filter","level":3,"score":0.6097000241279602},{"id":"https://openalex.org/C155911762","wikidata":"https://www.wikidata.org/wiki/Q422321","display_name":"Blueprint","level":2,"score":0.5758000016212463},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.52920001745224},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5249000191688538},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4519999921321869},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.383899986743927},{"id":"https://openalex.org/C68443243","wikidata":"https://www.wikidata.org/wiki/Q2786686","display_name":"Quartile","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C2992086627","wikidata":"https://www.wikidata.org/wiki/Q8046","display_name":"German economy","level":3,"score":0.30979999899864197},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2840000092983246},{"id":"https://openalex.org/C154775046","wikidata":"https://www.wikidata.org/wiki/Q188","display_name":"German","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2777999937534332},{"id":"https://openalex.org/C2078106","wikidata":"https://www.wikidata.org/wiki/Q14906620","display_name":"Accumulator (cryptography)","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2676999866962433}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/15741699261508760","doi":"https://doi.org/10.1177/15741699261508760","is_oa":false,"landing_page_url":"https://doi.org/10.1177/15741699261508760","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-c","anvur-scientific","cwts-core","jufo-1","poland-40","russia-white-list-3"],"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W231358793","https://openalex.org/W627307809","https://openalex.org/W1218120164","https://openalex.org/W1533212035","https://openalex.org/W1973798171","https://openalex.org/W1985710418","https://openalex.org/W1999190721","https://openalex.org/W2001299586","https://openalex.org/W2004482211","https://openalex.org/W2013879688","https://openalex.org/W2023856538","https://openalex.org/W2054379763","https://openalex.org/W2086258274","https://openalex.org/W2098944432","https://openalex.org/W2140348594","https://openalex.org/W2172525224","https://openalex.org/W2244091924","https://openalex.org/W2426112559","https://openalex.org/W2883145978","https://openalex.org/W2914773059","https://openalex.org/W2991285926","https://openalex.org/W4242401210","https://openalex.org/W4242638336","https://openalex.org/W4254640406","https://openalex.org/W4293801735","https://openalex.org/W4404196805","https://openalex.org/W4404364596","https://openalex.org/W4411591582"],"related_works":[],"abstract_inverted_index":{"The":[0,70,168],"classical":[1,97],"X-11":[2,34],"seasonal":[3,17,68,196],"adjustment":[4],"method":[5],"for":[6,16,79,88,164,179],"monthly":[7],"and":[8,66,99],"quarterly":[9],"data":[10,162,193],"contains":[11],"an":[12],"automatic":[13],"selection":[14,58,86,104],"routine":[15,21],"filters.":[18,69],"Although":[19],"this":[20,48],"has":[22,27],"a":[23,32,52,84,107,123],"long-standing":[24],"tradition,":[25],"it":[26],"not":[28],"been":[29],"adopted":[30],"in":[31,93,183],"recent":[33],"modification":[35],"tailored":[36],"to":[37,46,74,82,100,153],"the":[38,56,62,96,102,111,117,127,131,135,165,176,184,187,192],"specifics":[39],"of":[40,55,90,110,134,170,186],"sub-monthly":[41],"time":[42],"series.":[43],"We":[44,144],"seek":[45],"fill":[47],"gap":[49],"by":[50],"suggesting":[51],"generic":[53],"refurbishment":[54],"legacy":[57],"concept":[59],"based":[60,149],"upon":[61,150],"moving":[63,136,188],"seasonality":[64,137,189],"ratio":[65,138,190],"concurrent":[67],"key":[71],"idea":[72],"is":[73],"consider":[75,145],"multiple":[76,195],"derivation":[77],"principles":[78,92],"such":[80],"filters,":[81],"develop":[83],"preliminary":[85,112],"rule":[87,105],"each":[89],"these":[91],"line":[94],"with":[95,158],"concept,":[98],"obtain":[101],"final":[103,118],"through":[106],"proper":[108],"intersection":[109,148],"rules.":[113],"This":[114],"approach":[115],"stabilises":[116],"filter":[119],"choice":[120],"and,":[121],"as":[122],"by-product,":[124],"naturally":[125],"generates":[126],"warranted":[128],"thresholds":[129],"controlling":[130],"potential":[132],"recalculation":[133],"from":[139],"suitably":[140],"shortened":[141],"detrended":[142],"observations.":[143],"one":[146],"specific":[147],"threshold":[151],"quartiles":[152],"illustrate":[154],"our":[155],"proposed":[156],"blueprint":[157],"three":[159],"real-time":[160],"macroeconomic":[161],"examples":[163],"German":[166],"economy.":[167],"case":[169],"daily":[171],"electricity":[172],"consumption":[173],"particularly":[174],"highlights":[175],"general":[177],"need":[178],"additional":[180],"intermediate":[181],"steps":[182],"calculation":[185],"when":[191],"contain":[194],"patterns.":[197]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}