{"id":"https://openalex.org/W2591870309","doi":"https://doi.org/10.1109/lsp.2017.2722222","title":"A Study of the Allan Variance for Constant-Mean Nonstationary Processes","display_name":"A Study of the Allan Variance for Constant-Mean Nonstationary Processes","publication_year":2017,"publication_date":"2017-06-30","ids":{"openalex":"https://openalex.org/W2591870309","doi":"https://doi.org/10.1109/lsp.2017.2722222","mag":"2591870309"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2017.2722222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2722222","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1702.07795","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Haotian Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Haotian Xu","raw_affiliation_strings":["Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Stephane Guerrier","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephane Guerrier","raw_affiliation_strings":["Department of Statistics, Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Roberto Molinari","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roberto Molinari","raw_affiliation_strings":["Department of Statistics & Applied Probability, University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics & Applied Probability, University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yuming Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuming Zhang","raw_affiliation_strings":["Department of Statistics, Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6408,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72682226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"24","issue":"8","first_page":"1257","last_page":"1260"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.14949999749660492,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.14949999749660492,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T13928","display_name":"Advanced Sensor Technologies Research","score":0.12479999661445618,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12004","display_name":"Advanced Frequency and Time Standards","score":0.09839999675750732,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/allan-variance","display_name":"Allan variance","score":0.7400000095367432},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.6794999837875366},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.6642000079154968},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.6585999727249146},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6022999882698059},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5885000228881836},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5386000275611877},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.45649999380111694}],"concepts":[{"id":"https://openalex.org/C5722023","wikidata":"https://www.wikidata.org/wiki/Q1440227","display_name":"Allan variance","level":3,"score":0.7400000095367432},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.6794999837875366},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.6642000079154968},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6585999727249146},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6022999882698059},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5885000228881836},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5386000275611877},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47290000319480896},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43650001287460327},{"id":"https://openalex.org/C110405555","wikidata":"https://www.wikidata.org/wiki/Q1192209","display_name":"Stationary process","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.41839998960494995},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3522999882698059},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3400999903678894},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.32690000534057617},{"id":"https://openalex.org/C119340705","wikidata":"https://www.wikidata.org/wiki/Q1628597","display_name":"Analysis of covariance","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.28450000286102295},{"id":"https://openalex.org/C98991287","wikidata":"https://www.wikidata.org/wiki/Q5178895","display_name":"Covariance and correlation","level":5,"score":0.27649998664855957},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.27300000190734863},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.25459998846054077}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2017.2722222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2722222","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1702.07795","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1702.07795","pdf_url":"https://arxiv.org/pdf/1702.07795","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1702.07795","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1702.07795","pdf_url":"https://arxiv.org/pdf/1702.07795","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W612713307","https://openalex.org/W1598649019","https://openalex.org/W1996894524","https://openalex.org/W1997330647","https://openalex.org/W1999996900","https://openalex.org/W2010644321","https://openalex.org/W2131420149","https://openalex.org/W2189469324"],"related_works":[],"abstract_inverted_index":{"The":[0,36],"Allan":[1],"variance":[2,23],"(AV)":[3],"is":[4,41,70,130],"a":[5,143],"widely":[6,42],"used":[7,43],"quantity":[8,40,59,148],"in":[9,18,27,73,149],"areas":[10],"focusing":[11],"on":[12],"error":[13],"measurement":[14],"as":[15,17,30],"well":[16],"the":[19,55,80,90,94,102,124,128,136],"general":[20],"analysis":[21],"of":[22,38,50,57,79,93,146],"for":[24,63,108,126,142],"autocorrelated":[25],"processes":[26,66,99,125],"domains":[28],"such":[29],"engineering":[31],"and,":[32,72],"more":[33],"specifically,":[34],"metrology.":[35],"form":[37,92,119],"this":[39,58,117,147],"to":[44,84,96,122,132],"detect":[45],"noise":[46],"patterns":[47],"and":[48,139],"indications":[49],"stability":[51],"within":[52],"signals.":[53],"However,":[54],"properties":[56],"are":[60],"not":[61],"known":[62],"commonly":[64],"occurring":[65],"whose":[67],"covariance":[68],"structure":[69],"nonstationary":[71,98],"these":[74,134],"cases,":[75],"an":[76],"erroneous":[77],"interpretation":[78,145],"AV":[81,95,129],"could":[82],"lead":[83],"misleading":[85],"conclusions.":[86],"This":[87],"letter":[88],"generalizes":[89],"theoretical":[91],"some":[97],"while":[100],"at":[101],"same":[103],"time":[104],"being":[105],"valid":[106],"also":[107],"weakly":[109],"stationary":[110,137],"processes.":[111],"Some":[112],"simulation":[113],"examples":[114],"show":[115],"how":[116],"new":[118],"can":[120],"help":[121],"understand":[123],"which":[127],"able":[131],"distinguish":[133],"from":[135],"cases":[138],"hence":[140],"allow":[141],"better":[144],"applied":[150],"cases.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2017-03-16T00:00:00"}
