{"id":"https://openalex.org/W2067647652","doi":"https://doi.org/10.1109/cec.2014.6900660","title":"Evolutionary algorithms applied to likelihood function maximization during poisson, logistic, and Cox proportional hazards regression analysis","display_name":"Evolutionary algorithms applied to likelihood function maximization during poisson, logistic, and Cox proportional hazards regression analysis","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2067647652","doi":"https://doi.org/10.1109/cec.2014.6900660","mag":"2067647652"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2014.6900660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2014.6900660","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Congress on Evolutionary Computation (CEC)","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/A5030570150","display_name":"L. E. Peterson","orcid":"https://orcid.org/0000-0002-1187-0883"},"institutions":[{"id":"https://openalex.org/I1295876152","display_name":"Houston Methodist","ror":"https://ror.org/027zt9171","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1295876152"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Leif E. Peterson","raw_affiliation_strings":["Center for Biostatistics, Houston Methodist Research Institute, Houston, Texas, USA","Center for Biostatistics, Houston Methodist Research Institute, 6565 Fannin Street, Suite MGJ6-031, Houston, Texas 77030, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Biostatistics, Houston Methodist Research Institute, Houston, Texas, USA","institution_ids":["https://openalex.org/I1295876152"]},{"raw_affiliation_string":"Center for Biostatistics, Houston Methodist Research Institute, 6565 Fannin Street, Suite MGJ6-031, Houston, Texas 77030, USA","institution_ids":["https://openalex.org/I1295876152"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5030570150"],"corresponding_institution_ids":["https://openalex.org/I1295876152"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12870662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"127","issue":null,"first_page":"1054","last_page":"1061"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9962999820709229,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9962999820709229,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9866999983787537,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.5288953185081482},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5212560296058655},{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.5094955563545227},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4898183047771454},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4794444143772125},{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.4677850008010864},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42797398567199707},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.42760467529296875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3896751403808594},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.21463564038276672}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5288953185081482},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5212560296058655},{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.5094955563545227},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4898183047771454},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4794444143772125},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.4677850008010864},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42797398567199707},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.42760467529296875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3896751403808594},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.21463564038276672}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2014.6900660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2014.6900660","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320333034","display_name":"Center of Mathematical Sciences and Applications, Harvard University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1492640216","https://openalex.org/W1497256448","https://openalex.org/W1973948212","https://openalex.org/W1975009952","https://openalex.org/W2002592134","https://openalex.org/W2004617458","https://openalex.org/W2021467330","https://openalex.org/W2024060531","https://openalex.org/W2039568841","https://openalex.org/W2082102453","https://openalex.org/W2084792706","https://openalex.org/W2152195021","https://openalex.org/W2409729586","https://openalex.org/W2796700885","https://openalex.org/W3149025087","https://openalex.org/W4298222310","https://openalex.org/W6714290826"],"related_works":["https://openalex.org/W2611031068","https://openalex.org/W1704347466","https://openalex.org/W4283017538","https://openalex.org/W1996936972","https://openalex.org/W1545275724","https://openalex.org/W2802707792","https://openalex.org/W2075777916","https://openalex.org/W3021699548","https://openalex.org/W2569979269","https://openalex.org/W3095745430"],"abstract_inverted_index":{"Metaheuristics":[0],"based":[1],"on":[2],"genetic":[3],"algorithms":[4],"(GA),":[5],"covariance":[6],"matrix":[7],"self-adaptation":[8],"evolution":[9],"strategies":[10],"(CMSA-ES),":[11],"particle":[12],"swarm":[13],"optimization":[14,19],"(PSO),":[15],"and":[16,29,37,51,71,86,92,114],"ant":[17],"colony":[18],"(ACO)":[20],"were":[21,54,60],"used":[22],"for":[23,26,34,84],"minimizing":[24],"deviance":[25],"Poisson":[27],"regression":[28,36,48],"maximizing":[30],"the":[31,78,97,111,118],"log-likelihood":[32,112],"function":[33],"logistic":[35],"Cox":[38],"proportional":[39],"hazards":[40],"regression.":[41],"We":[42],"observed":[43],"that,":[44],"in":[45,61],"terms":[46],"of":[47,75,110,117],"coefficients,":[49],"CMSA-ES":[50,85,95],"PSO":[52,87],"metaheuristics":[53],"able":[55],"to":[56,77],"obtain":[57],"solutions":[58],"that":[59],"better":[62],"agreement":[63],"with":[64,69,90],"Newton-Raphson":[65],"(NR)":[66],"when":[67,88],"compared":[68,89],"GA":[70],"ACO.":[72],"The":[73],"rate":[74],"convergence":[76],"NR":[79],"solution":[80],"was":[81,96],"also":[82],"faster":[83],"ACO":[91],"GA.":[93],"Overall,":[94],"best-performing":[98],"method":[99],"used.":[100],"Key":[101],"factors":[102],"which":[103],"strongly":[104],"influence":[105],"performance":[106],"are":[107],"multicollinearity,":[108],"shape":[109],"gradient,":[113],"positive":[115],"definiteness":[116],"Hessian":[119],"matrix.":[120]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
