{"id":"https://openalex.org/W2086716710","doi":"https://doi.org/10.1109/sam.2012.6250512","title":"Natural order recovery for banded covariance models","display_name":"Natural order recovery for banded covariance models","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2086716710","doi":"https://doi.org/10.1109/sam.2012.6250512","mag":"2086716710"},"language":"en","primary_location":{"id":"doi:10.1109/sam.2012.6250512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam.2012.6250512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM)","raw_type":"proceedings-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/A5033945494","display_name":"Benjamin T. Rolfs","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Benjamin T. Rolfs","raw_affiliation_strings":["Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA","Institute for computational and mathematical engineering, stanford university, ca 94305, usa#TAB#"],"affiliations":[{"raw_affiliation_string":"Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Institute for computational and mathematical engineering, stanford university, ca 94305, usa#TAB#","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091424272","display_name":"Bala Rajaratnam","orcid":"https://orcid.org/0000-0003-2570-8059"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bala Rajaratnam","raw_affiliation_strings":["Department of Statistics, Stanford University, Stanford, CA, USA","Department of Statistics, Stanford University, CA 94305 USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Statistics, Stanford University, CA 94305 USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033945494"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.63526777,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.70136324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"365","last_page":"368"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9995999932289124,"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":0.9995999932289124,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9977999925613403,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.8558710217475891},{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.6424265503883362},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6320661306381226},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.6294345259666443},{"id":"https://openalex.org/keywords/covariance-function","display_name":"Covariance function","score":0.5555296540260315},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5327069163322449},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5150913596153259},{"id":"https://openalex.org/keywords/mat\u00e9rn-covariance-function","display_name":"Mat\u00e9rn covariance function","score":0.49753955006599426},{"id":"https://openalex.org/keywords/rational-quadratic-covariance-function","display_name":"Rational quadratic covariance function","score":0.4929027557373047},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49099424481391907},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4725971817970276},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4697834551334381},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4606713056564331},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.437389999628067},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35137519240379333},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34433966875076294},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2564634084701538}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.8558710217475891},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.6424265503883362},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6320661306381226},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.6294345259666443},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.5555296540260315},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5327069163322449},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5150913596153259},{"id":"https://openalex.org/C118006245","wikidata":"https://www.wikidata.org/wiki/Q6792079","display_name":"Mat\u00e9rn covariance function","level":5,"score":0.49753955006599426},{"id":"https://openalex.org/C148893098","wikidata":"https://www.wikidata.org/wiki/Q7295778","display_name":"Rational quadratic covariance function","level":5,"score":0.4929027557373047},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49099424481391907},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4725971817970276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4697834551334381},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4606713056564331},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.437389999628067},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35137519240379333},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34433966875076294},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2564634084701538},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sam.2012.6250512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sam.2012.6250512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332359","display_name":"Office of Science","ror":"https://ror.org/00mmn6b08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W85690038","https://openalex.org/W1502421007","https://openalex.org/W2020370559","https://openalex.org/W2052386156","https://openalex.org/W2095420020","https://openalex.org/W2121454540","https://openalex.org/W2130351130","https://openalex.org/W2132555912","https://openalex.org/W2151128232","https://openalex.org/W3098045107","https://openalex.org/W3101788651"],"related_works":["https://openalex.org/W2022823194","https://openalex.org/W2126916073","https://openalex.org/W3211883524","https://openalex.org/W2109377650","https://openalex.org/W1987404909","https://openalex.org/W4386993326","https://openalex.org/W1627656821","https://openalex.org/W3025277714","https://openalex.org/W2018001152","https://openalex.org/W2050026105"],"abstract_inverted_index":{"Banded":[0,14],"covariance":[1,11,16,34,109],"models":[2,17],"have":[3,24],"recently":[4],"received":[5],"attention":[6],"in":[7,46,73],"the":[8,47,106,131],"high":[9],"dimensional":[10],"estimation":[12],"literature.":[13],"inverse":[15,108],"correspond":[18],"to":[19],"autoregressive":[20],"processes":[21],"and":[22,27,123,126],"thus":[23],"a":[25,37,54,65,91],"simple":[26],"intuitive":[28],"interpretation,":[29],"offering":[30],"insight":[31],"into":[32],"underlying":[33,107],"structure.":[35],"While":[36],"body":[38],"of":[39,53,97],"asymptotic":[40],"results":[41,129],"for":[42,67,94],"banded":[43,112],"estimators":[44],"exists":[45],"literature,":[48],"these":[49],"methods":[50],"assume":[51],"knowledge":[52],"natural":[55],"variable":[56],"ordering.":[57],"Although":[58],"such":[59],"an":[60],"ordering":[61],"may":[62],"be":[63,78,84],"known":[64],"priori,":[66],"example":[68],"with":[69,130],"time":[70],"series":[71],"data,":[72,125],"other":[74,133],"settings":[75],"it":[76],"must":[77],"inferred":[79],"before":[80],"banding":[81],"approaches":[82],"can":[83],"applied.":[85],"In":[86],"this":[87],"paper,":[88],"we":[89],"present":[90],"new":[92],"method":[93],"recovering":[95],"order":[96,135],"random":[98],"variables":[99],"based":[100],"on":[101,120],"Gaussian":[102],"graphical":[103],"modelling":[104],"when":[105],"matrices":[110],"are":[111],"or":[113],"differentially":[114],"banded.":[115],"We":[116],"demonstrate":[117],"our":[118,128],"algorithm":[119],"both":[121],"synthetic":[122],"real":[124],"compare":[127],"only":[132],"published":[134],"recovery":[136],"method.":[137]},"counts_by_year":[{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
