{"id":"https://openalex.org/W3043738449","doi":"https://doi.org/10.1109/tetc.2020.3009295","title":"Sparse Logistic Maximum Likelihood Estimation for Optimal Well-Being Determinants","display_name":"Sparse Logistic Maximum Likelihood Estimation for Optimal Well-Being Determinants","publication_year":2020,"publication_date":"2020-07-14","ids":{"openalex":"https://openalex.org/W3043738449","doi":"https://doi.org/10.1109/tetc.2020.3009295","mag":"3043738449"},"language":"en","primary_location":{"id":"doi:10.1109/tetc.2020.3009295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetc.2020.3009295","pdf_url":null,"source":{"id":"https://openalex.org/S2496326734","display_name":"IEEE Transactions on Emerging Topics in Computing","issn_l":"2168-6750","issn":["2168-6750","2376-4562"],"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 Emerging Topics in Computing","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/A5091201700","display_name":"Jianyi Lin","orcid":"https://orcid.org/0000-0002-3299-448X"},"institutions":[{"id":"https://openalex.org/I176601375","display_name":"Khalifa University of Science and Technology","ror":"https://ror.org/05hffr360","country_code":"AE","type":"education","lineage":["https://openalex.org/I176601375"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Jianyi Lin","raw_affiliation_strings":["Department of Mathematics, Khalifa University of Science and Technology, Abu Dhabi, UAE"],"raw_orcid":"https://orcid.org/0000-0002-3299-448X","affiliations":[{"raw_affiliation_string":"Department of Mathematics, Khalifa University of Science and Technology, Abu Dhabi, UAE","institution_ids":["https://openalex.org/I176601375"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078357034","display_name":"Emiliano Sironi","orcid":"https://orcid.org/0000-0001-9129-3133"},"institutions":[{"id":"https://openalex.org/I103320735","display_name":"Universit\u00e0 Cattolica del Sacro Cuore","ror":"https://ror.org/03h7r5v07","country_code":"IT","type":"education","lineage":["https://openalex.org/I103320735"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Emiliano Sironi","raw_affiliation_strings":["Department of Statistical Sciences, Universit\u00e0 Cattolica del Sacro Cuore, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0001-9129-3133","affiliations":[{"raw_affiliation_string":"Department of Statistical Sciences, Universit\u00e0 Cattolica del Sacro Cuore, Milan, Italy","institution_ids":["https://openalex.org/I103320735"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.6282,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72482451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9","issue":"3","first_page":"1316","last_page":"1327"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10475","display_name":"Psychological Well-being and Life Satisfaction","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10475","display_name":"Psychological Well-being and Life Satisfaction","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10446","display_name":"Income, Poverty, and Inequality","score":0.9620000123977661,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.958899974822998,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.7330983877182007},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5791842341423035},{"id":"https://openalex.org/keywords/generalized-linear-model","display_name":"Generalized linear model","score":0.502446174621582},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.4930393397808075},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4506049156188965},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43726468086242676},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4251539409160614},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4191017746925354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36793628334999084},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3575817942619324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3279392123222351}],"concepts":[{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.7330983877182007},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5791842341423035},{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.502446174621582},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.4930393397808075},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4506049156188965},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43726468086242676},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4251539409160614},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4191017746925354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36793628334999084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3575817942619324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3279392123222351},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetc.2020.3009295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetc.2020.3009295","pdf_url":null,"source":{"id":"https://openalex.org/S2496326734","display_name":"IEEE Transactions on Emerging Topics in Computing","issn_l":"2168-6750","issn":["2168-6750","2376-4562"],"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 Emerging Topics in Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W744363352","https://openalex.org/W824512843","https://openalex.org/W1492578514","https://openalex.org/W1523985187","https://openalex.org/W1585338386","https://openalex.org/W1591116419","https://openalex.org/W1966603703","https://openalex.org/W1966607782","https://openalex.org/W1977442524","https://openalex.org/W1992646537","https://openalex.org/W2010333962","https://openalex.org/W2011039300","https://openalex.org/W2078205970","https://openalex.org/W2089783325","https://openalex.org/W2098341956","https://openalex.org/W2115549875","https://openalex.org/W2125786679","https://openalex.org/W2127259621","https://openalex.org/W2129812935","https://openalex.org/W2136751920","https://openalex.org/W2144006746","https://openalex.org/W2149232116","https://openalex.org/W2149416133","https://openalex.org/W2162302372","https://openalex.org/W2170331458","https://openalex.org/W2171427501","https://openalex.org/W2258957433","https://openalex.org/W2296616510","https://openalex.org/W2318600406","https://openalex.org/W2394499918","https://openalex.org/W2564898197","https://openalex.org/W2566663219","https://openalex.org/W2578295730","https://openalex.org/W2740950460","https://openalex.org/W2778793929","https://openalex.org/W2780707477","https://openalex.org/W2792065904","https://openalex.org/W2883170753","https://openalex.org/W2903718010","https://openalex.org/W2910237298","https://openalex.org/W2971788173","https://openalex.org/W3099257477","https://openalex.org/W3124068636","https://openalex.org/W3124205685","https://openalex.org/W3126849616","https://openalex.org/W4235713725","https://openalex.org/W4241369862","https://openalex.org/W4250955649","https://openalex.org/W4252468642","https://openalex.org/W4301014524","https://openalex.org/W4388323214","https://openalex.org/W6629504650","https://openalex.org/W6677446445","https://openalex.org/W6679164698","https://openalex.org/W6680288239","https://openalex.org/W6731256111","https://openalex.org/W6742206820","https://openalex.org/W6767293667"],"related_works":["https://openalex.org/W3194539120","https://openalex.org/W2937631562","https://openalex.org/W4361795583","https://openalex.org/W3195168932","https://openalex.org/W1996541855","https://openalex.org/W2979979539","https://openalex.org/W2101819884","https://openalex.org/W2803710604","https://openalex.org/W3127425528","https://openalex.org/W4321636153"],"abstract_inverted_index":{"Optimal":[0],"well-being":[1,26,111],"is":[2,80],"a":[3,54,67,177],"new":[4],"multi-dimensional":[5],"construct,":[6],"which":[7,107],"incorporates":[8],"the":[9,22,41,59,75,94,103,115,138,146,168,171,190,194],"well-known":[10],"preexisting":[11],"notions":[12],"of":[13,24,43,66,93,105,114,135,140,148,167,170,174,193],"subjective":[14],"and":[15,82,132],"psychological":[16],"well-being.":[17,150],"Classical":[18],"models":[19,33],"for":[20,58,143],"describing":[21],"predictors":[23,44,127],"optimal":[25,110,149],"binary":[27],"response":[28],"variable":[29],"are":[30],"generalized":[31],"linear":[32],"(GLM),":[34],"such":[35],"as":[36,189],"logistic":[37,161,184],"regression":[38,60,118],"model.":[39],"Since":[40],"number":[42],"might":[45],"be":[46],"relatively":[47],"large":[48],"in":[49,99,137,165,176],"these":[50],"models,":[51],"we":[52],"devise":[53],"sparse":[55,69,81,117,160],"optimization":[56,195],"method":[57],"problem":[61,196],"based":[62],"on":[63],"subsequent":[64],"iterations":[65],"suitable":[68],"quadratic":[70],"approximant":[71],"problem,":[72],"so":[73],"that":[74,124,159],"resulting":[76],"parameter":[77,156],"vector":[78,173],"estimate":[79],"indicates":[83],"few":[84,125],"significant":[85],"predictors.":[86],"We":[87],"conduct":[88],"empirical":[89],"assessments":[90],"using":[91],"data":[92,121,130],"European":[95],"Social":[96],"Survey":[97],"(ESS),":[98],"order":[100],"to":[101,182],"identify":[102],"set":[104],"determinants":[106],"better":[108,164],"predict":[109],"by":[112],"means":[113],"proposed":[116],"method.":[119],"ESS":[120],"analysis":[122],"confirms":[123],"selected":[126],"provide":[128],"good":[129],"interpretation":[131],"no":[133],"loss":[134],"information":[136],"frequency":[139],"correct":[141],"classification":[142],"people":[144],"meeting":[145],"criteria":[147],"Moreover,":[151],"simulations":[152],"with":[153],"different":[154],"structural":[155,191],"values":[157],"indicate":[158],"model":[162],"performs":[163],"terms":[166],"estimation":[169],"true":[172],"parameters":[175],"more":[178],"parsimonious":[179],"setting":[180],"compared":[181],"classical":[183],"regression.":[185],"The":[186],"benefits":[187],"increase":[188],"sparsity":[192],"becomes":[197],"stronger.":[198]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}