{"id":"https://openalex.org/W4393241212","doi":"https://doi.org/10.1109/tsp.2024.3382407","title":"Optimal Bayesian Regression With Vector Autoregressive Data Dependency","display_name":"Optimal Bayesian Regression With Vector Autoregressive Data Dependency","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4393241212","doi":"https://doi.org/10.1109/tsp.2024.3382407"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2024.3382407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3382407","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-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/A5060198824","display_name":"Samira Reihanian","orcid":"https://orcid.org/0009-0001-5299-8584"},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":true,"raw_author_name":"Samira Reihanian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112221423","display_name":"Edward R. Dougherty","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Edward R. Dougherty","raw_affiliation_strings":["Center for Bioinformatics and Genomic Systems Engineering, Department of Electrical and Computer Engineering, Texas A&#x0026;M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Center for Bioinformatics and Genomic Systems Engineering, Department of Electrical and Computer Engineering, Texas A&#x0026;M University, College Station, TX, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040086890","display_name":"Amin Zollanvari","orcid":"https://orcid.org/0000-0002-9172-8413"},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Amin Zollanvari","raw_affiliation_strings":["Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060198824"],"corresponding_institution_ids":["https://openalex.org/I60559429"],"apc_list":null,"apc_paid":null,"fwci":5.2755,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.95789952,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"1854","last_page":"1864"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9951000213623047,"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":0.9951000213623047,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9918000102043152,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9817000031471252,"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/autoregressive-model","display_name":"Autoregressive model","score":0.6682192087173462},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6117739081382751},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5737705230712891},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5720713138580322},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4827698767185211},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4592350423336029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4507170617580414},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4042343497276306},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.39535394310951233},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.38579490780830383},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3726775646209717},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29837673902511597}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6682192087173462},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6117739081382751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5737705230712891},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5720713138580322},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4827698767185211},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4592350423336029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4507170617580414},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4042343497276306},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.39535394310951233},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.38579490780830383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3726775646209717},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29837673902511597}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2024.3382407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3382407","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W181198635","https://openalex.org/W2013276223","https://openalex.org/W2024649135","https://openalex.org/W2039903398","https://openalex.org/W2053492670","https://openalex.org/W2065175896","https://openalex.org/W2144037222","https://openalex.org/W2148557226","https://openalex.org/W2334037248","https://openalex.org/W2490800645","https://openalex.org/W2513723748","https://openalex.org/W2770058355","https://openalex.org/W2891293381","https://openalex.org/W2933554143","https://openalex.org/W2943118511","https://openalex.org/W2947626232","https://openalex.org/W3085820219","https://openalex.org/W4205687621","https://openalex.org/W4206180546","https://openalex.org/W4212863985","https://openalex.org/W4238240379","https://openalex.org/W4312258136","https://openalex.org/W4388215482"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W2621086889"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3],"derive":[4],"a":[5,27,58],"closed-form":[6],"analytic":[7],"representation":[8],"of":[9,32,42],"the":[10,15,39,43,48,53,83,93],"optimal":[11,55],"Bayesian":[12],"regression":[13],"when":[14],"data":[16,80,94],"are":[17,95],"generated":[18],"from":[19],"VAR(":[20],"<italic":[21,34,63],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[22,35,64],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">p</i>":[23,36,65],"),":[24],"which":[25,68],"is":[26],"multidimensional":[28],"vector":[29],"autoregressive":[30],"process":[31],"order":[33],".":[37],"Given":[38],"covariance":[40],"matrix":[41],"underlying":[44],"Gaussian":[45],"white-noise":[46],"process,":[47],"developed":[49,84],"regressor":[50,56,85],"reduces":[51],"to":[52],"conventional":[54],"for":[57],"non-informative":[59],"prior":[60],"and":[61,78],"setting":[62],"=":[66],"0,":[67],"implies":[69],"independent":[70],"data.":[71],"Our":[72],"empirical":[73],"results":[74],"using":[75],"both":[76],"synthetic":[77],"real":[79],"show":[81],"that":[82],"can":[86],"effectively":[87],"be":[88],"used":[89],"in":[90],"situations":[91],"where":[92],"sequentially":[96],"dependent.":[97]},"counts_by_year":[{"year":2025,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}