{"id":"https://openalex.org/W2127074645","doi":"https://doi.org/10.1109/icassp.2005.1415944","title":"Parameter estimation with missing data via equalization-maximization","display_name":"Parameter estimation with missing data via equalization-maximization","publication_year":2006,"publication_date":"2006-10-11","ids":{"openalex":"https://openalex.org/W2127074645","doi":"https://doi.org/10.1109/icassp.2005.1415944","mag":"2127074645"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1415944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","raw_type":"proceedings-article"},"type":"conference-paper","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/A5007877889","display_name":"Petre Stoica","orcid":"https://orcid.org/0000-0002-7957-3711"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Petre Stoica","raw_affiliation_strings":["Department of Information Technology, University of Uppsala, Uppsala, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, University of Uppsala, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000935553","display_name":"Luzhou Xu","orcid":"https://orcid.org/0000-0003-1934-149X"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luzhou Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100402538","display_name":"Jian Li","orcid":"https://orcid.org/0000-0002-7725-4346"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5605,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.81940299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"4","issue":null,"first_page":"57","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9954000115394592,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9954000115394592,"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":0.9901000261306763,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.987500011920929,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.8169326782226562},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.719135582447052},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7178384065628052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.616849958896637},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6119437217712402},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6020976901054382},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5777152180671692},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.5471592545509338},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5226376056671143},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4687880277633667},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4633752405643463},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4473857879638672},{"id":"https://openalex.org/keywords/equalization","display_name":"Equalization (audio)","score":0.4348592162132263},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4330523908138275},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.40682539343833923},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2967243194580078},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27217358350753784},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17656508088111877},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07935571670532227}],"concepts":[{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.8169326782226562},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.719135582447052},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7178384065628052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.616849958896637},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6119437217712402},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6020976901054382},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5777152180671692},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.5471592545509338},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5226376056671143},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4687880277633667},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4633752405643463},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4473857879638672},{"id":"https://openalex.org/C75755367","wikidata":"https://www.wikidata.org/wiki/Q104531076","display_name":"Equalization (audio)","level":3,"score":0.4348592162132263},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4330523908138275},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40682539343833923},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2967243194580078},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27217358350753784},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17656508088111877},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07935571670532227},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2005.1415944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415944","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W173611639","https://openalex.org/W2044758663","https://openalex.org/W2049633694","https://openalex.org/W2083704637","https://openalex.org/W2084833562","https://openalex.org/W2165324123","https://openalex.org/W2480680997"],"related_works":["https://openalex.org/W1978153144","https://openalex.org/W102848802","https://openalex.org/W2982058819","https://openalex.org/W2130734797","https://openalex.org/W2172249169","https://openalex.org/W3176361882","https://openalex.org/W2122958477","https://openalex.org/W2014532259","https://openalex.org/W4252706329","https://openalex.org/W2371827284"],"abstract_inverted_index":{"The":[0],"expectation-maximization":[1],"(EM)":[2],"algorithm":[3,31,54],"is":[4],"often":[5],"used":[6],"in":[7,55,63,87],"maximum":[8],"likelihood":[9],"(ML)":[10],"estimation":[11,34,95],"problems":[12,35],"with":[13,36,73],"missing":[14,37,78],"data.":[15],"However,":[16],"EM":[17,86],"can":[18],"be":[19,47],"rather":[20],"slow":[21],"to":[22,46],"converge.":[23],"In":[24,80],"this":[25],"paper,":[26],"we":[27,40],"introduce":[28],"a":[29,56,68,74,93],"new":[30],"for":[32],"parameter":[33],"data,":[38],"which":[39],"call":[41],"equalization-maximization":[42],"(EqM)":[43],"(for":[44],"reasons":[45],"explained":[48],"later).":[49],"We":[50],"derive":[51],"the":[52,64,81],"EqM":[53,84],"general":[57],"context":[58],"and":[59],"illustrate":[60],"its":[61],"use":[62],"specific":[65],"case":[66],"of":[67,77,89],"Gaussian":[69],"autoregressive":[70],"time":[71],"series":[72],"varying":[75],"amount":[76],"observations.":[79],"presented":[82],"examples,":[83],"outperforms":[85],"terms":[88],"computational":[90],"speed,":[91],"at":[92],"comparable":[94],"performance.":[96]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
