{"id":"https://openalex.org/W2157857149","doi":"https://doi.org/10.1109/tpami.1987.4767959","title":"Decision-Directed Multivariate Empirical Bayes Classification with Nonstationary Priors","display_name":"Decision-Directed Multivariate Empirical Bayes Classification with Nonstationary Priors","publication_year":1987,"publication_date":"1987-09-01","ids":{"openalex":"https://openalex.org/W2157857149","doi":"https://doi.org/10.1109/tpami.1987.4767959","mag":"2157857149","pmid":"https://pubmed.ncbi.nlm.nih.gov/21869423"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.1987.4767959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.1987.4767959","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5091717294","display_name":"Wynn C. Stirling","orcid":"https://orcid.org/0000-0002-4710-4363"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wynn C. Stirling","raw_affiliation_strings":["Department of Electrical Engineering, Brigham Young University, Provo, UT 84602","Department of Electrical Engineering, Brigham Young University, Provo, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Brigham Young University, Provo, UT 84602","institution_ids":["https://openalex.org/I100005738"]},{"raw_affiliation_string":"Department of Electrical Engineering, Brigham Young University, Provo, UT, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027055000","display_name":"A. Lee Swindlehurst","orcid":"https://orcid.org/0000-0002-0521-3107"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Lee Swindlehurst","raw_affiliation_strings":["Department of Electrical Engineering, Brigham Young University, Provo, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Brigham Young University, Provo, UT, USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.1798776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"PAMI-9","issue":"5","first_page":"644","last_page":"660"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10320","display_name":"Neural Networks and Applications","score":0.9927999973297119,"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/prior-probability","display_name":"Prior probability","score":0.6502642631530762},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5084449052810669},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5068073868751526},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.4796174466609955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.479155957698822},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4462767243385315},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.44042885303497314},{"id":"https://openalex.org/keywords/inverse-wishart-distribution","display_name":"Inverse-Wishart distribution","score":0.4313923716545105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3950890600681305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3664274215698242},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.3324401378631592},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32732218503952026},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.2822611331939697},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24929696321487427},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.2086258828639984}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6502642631530762},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5084449052810669},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5068073868751526},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.4796174466609955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.479155957698822},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4462767243385315},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.44042885303497314},{"id":"https://openalex.org/C40851411","wikidata":"https://www.wikidata.org/wiki/Q3258368","display_name":"Inverse-Wishart distribution","level":4,"score":0.4313923716545105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3950890600681305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3664274215698242},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.3324401378631592},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32732218503952026},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.2822611331939697},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24929696321487427},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2086258828639984},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tpami.1987.4767959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.1987.4767959","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:21869423","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21869423","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.720.3690","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.720.3690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://newport.eecs.uci.edu/%7Eswindle/pubs/DecisionDirectedMultivariate.pdf","raw_type":"text"},{"id":"pmh:oai:scholarsarchive.byu.edu:facpub-1743","is_oa":false,"landing_page_url":"https://scholarsarchive.byu.edu/facpub/744","pdf_url":null,"source":{"id":"https://openalex.org/S4377196308","display_name":"ScholarsArchive  (Brigham Young University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I100005738","host_organization_name":"Brigham Young University","host_organization_lineage":["https://openalex.org/I100005738"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1590636096","https://openalex.org/W1599798800","https://openalex.org/W1969879893","https://openalex.org/W1979771630","https://openalex.org/W1993393237","https://openalex.org/W1996411376","https://openalex.org/W2011871194","https://openalex.org/W2040502719","https://openalex.org/W2043095810","https://openalex.org/W2046386993","https://openalex.org/W2054360186","https://openalex.org/W2070836513","https://openalex.org/W2098384215","https://openalex.org/W2102280038","https://openalex.org/W2105666699","https://openalex.org/W2111132411","https://openalex.org/W2111316763","https://openalex.org/W2111942506","https://openalex.org/W2143724853","https://openalex.org/W2144579212","https://openalex.org/W2148237299","https://openalex.org/W2152723400","https://openalex.org/W2161345557","https://openalex.org/W2796325984","https://openalex.org/W2799137445","https://openalex.org/W4229844634","https://openalex.org/W4249214388","https://openalex.org/W4396738162","https://openalex.org/W6635437809","https://openalex.org/W6635823994"],"related_works":["https://openalex.org/W3049713613","https://openalex.org/W4283770175","https://openalex.org/W1839961359","https://openalex.org/W2075146114","https://openalex.org/W2100805585","https://openalex.org/W2913857634","https://openalex.org/W2087278778","https://openalex.org/W4378464991","https://openalex.org/W1987859003","https://openalex.org/W1570411980"],"abstract_inverted_index":{"A":[0],"decision-directed":[1],"learning":[2],"strategy":[3],"is":[4,26,56],"presented":[5],"to":[6,43,90,100,116],"recursively":[7],"estimate":[8,44,105],"(i.e.,":[9],"track)":[10],"the":[11,30,45,49,66,76,81,85,91,101,107,118,121],"time-varying":[12],"a":[13,17,34,70],"priori":[14],"distribution":[15,32],"for":[16,65],"multivariate":[18,71],"empirical":[19],"Bayes":[20],"adaptive":[21],"classification":[22],"rule.":[23],"The":[24,54],"problem":[25],"formulated":[27],"by":[28,58,94],"modeling":[29],"prior":[31,108],"as":[33],"finite-state":[35],"vector":[36,68],"Markov":[37],"chain":[38],"and":[39,98],"using":[40],"past":[41,96],"decisions":[42,97],"time":[46],"evolution":[47],"of":[48,51,69,84,106,120],"state":[50],"this":[52],"chain.":[53],"solution":[55],"obtained":[57],"implementing":[59],"an":[60],"exact":[61],"recursive":[62],"nonlinear":[63,102],"estimator":[64,79],"rate":[67],"discrete-time":[72],"point":[73],"process":[74,87],"representing":[75],"decisions.":[77],"This":[78],"obtains":[80],"Doob":[82],"decomposition":[83],"decision":[86],"with":[88],"respect":[89],"a-field":[92],"generated":[93],"all":[95],"corresponds":[99],"least":[103],"squares":[104],"distribution.":[109],"Monte":[110],"Carlo":[111],"simulation":[112],"results":[113],"are":[114],"provided":[115],"assess":[117],"performance":[119],"estimator.":[122]},"counts_by_year":[],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
