{"id":"https://openalex.org/W4389471302","doi":"https://doi.org/10.1007/s00180-026-01745-3","title":"Bayesian variable selection in sample selection models using spike-and-slab priors","display_name":"Bayesian variable selection in sample selection models using spike-and-slab priors","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W4389471302","doi":"https://doi.org/10.1007/s00180-026-01745-3","pmid":"https://pubmed.ncbi.nlm.nih.gov/42147122"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-026-01745-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-026-01745-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01745-3.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01745-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076253246","display_name":"Adam Iqbal","orcid":"https://orcid.org/0009-0005-0572-2381"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Adam J. Iqbal","raw_affiliation_strings":["Department of Mathematical Sciences, University of Durham, Stockton Road, Durham, DH1 3LE UK"],"raw_orcid":"https://orcid.org/0009-0005-0572-2381","affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Durham, Stockton Road, Durham, DH1 3LE UK","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061374096","display_name":"Emmanuel Ogundimu","orcid":"https://orcid.org/0000-0001-9252-9275"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Emmanuel O. Ogundimu","raw_affiliation_strings":["Department of Mathematical Sciences, University of Durham, Stockton Road, Durham, DH1 3LE UK"],"raw_orcid":"https://orcid.org/0000-0001-9252-9275","affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Durham, Stockton Road, Durham, DH1 3LE UK","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055000887","display_name":"Francisco J. Rubio","orcid":"https://orcid.org/0000-0001-7183-8407"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"F. Javier Rubio","raw_affiliation_strings":["Department of Statistical Science, University College London, 1-19 Torrington Place, London, WC1E 7HB UK"],"raw_orcid":"https://orcid.org/0000-0001-7183-8407","affiliations":[{"raw_affiliation_string":"Department of Statistical Science, University College London, 1-19 Torrington Place, London, WC1E 7HB UK","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076253246"],"corresponding_institution_ids":["https://openalex.org/I190082696"],"apc_list":{"value":3090,"currency":"USD","value_usd":3090},"apc_paid":{"value":3090,"currency":"USD","value_usd":3090},"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.00668556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"41","issue":"4","first_page":"81","last_page":"81"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9904999732971191,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9904999732971191,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9873999953269958,"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":0.9828000068664551,"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":0.6938640475273132},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6723432540893555},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6351636648178101},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5975991487503052},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5630865693092346},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.5617163777351379},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.540600597858429},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5164282917976379},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.503004252910614},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4936893880367279},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.46977847814559937},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.45340555906295776},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4383571147918701},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.415620893239975},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.41048139333724976}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6938640475273132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6723432540893555},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6351636648178101},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5975991487503052},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5630865693092346},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.5617163777351379},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.540600597858429},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5164282917976379},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.503004252910614},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4936893880367279},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.46977847814559937},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.45340555906295776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4383571147918701},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.415620893239975},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.41048139333724976},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s00180-026-01745-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-026-01745-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01745-3.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},{"id":"pmid:42147122","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42147122","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":"Computational statistics","raw_type":null},{"id":"pmh:oai:arXiv.org:2312.03538","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.03538","pdf_url":"https://arxiv.org/pdf/2312.03538","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:13171941","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13171941/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13171941/pdf/180_2026_Article_1745.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Comput Stat","raw_type":"Text"},{"id":"doi:10.48550/arxiv.2312.03538","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2312.03538","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1007/s00180-026-01745-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-026-01745-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01745-3.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2311376767","display_name":"Additional Funding for Mathematical Sciences: Heilbronn Institute for Mathematical Research","funder_award_id":"EP/V521917/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320337380","display_name":"Division of Mathematical Sciences","ror":"https://ror.org/051fftw81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389471302.pdf","grobid_xml":"https://content.openalex.org/works/W4389471302.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W3168675052","https://openalex.org/W4394396474","https://openalex.org/W2799769600","https://openalex.org/W3015383640"],"abstract_inverted_index":{"Abstract":[0],"Sample":[1],"selection":[2,36,85,111,146,149],"models":[3],"are":[4,16],"a":[5,157,181,186],"widely":[6],"used":[7],"approach":[8],"for":[9,155],"correcting":[10],"bias":[11],"caused":[12],"by":[13],"data":[14],"that":[15,27,33,76,105],"missing":[17],"not":[18],"at":[19],"random.":[20],"Their":[21],"formulation":[22],"requires":[23],"specifying":[24],"the":[25,29,35,50,56,91,103,108,118,167,174,177],"variables":[26,54,83,104],"influence":[28],"outcome":[30,92,109],"and":[31,110,184,191],"those":[32],"drive":[34],"process.":[37],"This":[38],"specification":[39],"is":[40,164],"often":[41],"based":[42],"on":[43,90,117],"expert":[44],"knowledge,":[45],"which":[46,81,122,163],"can":[47,123],"result":[48],"in":[49,80,126,147],"inclusion":[51],"of":[52,58,93,139,169,176],"irrelevant":[53],"or":[55],"omission":[57],"important":[59],"ones.":[60],"Moreover,":[61],"to":[62,101,128,142,166],"avoid":[63],"inferential":[64],"problems":[65],"such":[66],"as":[67],"practical":[68,170],"non-identifiability,":[69],"practitioners":[70],"frequently":[71],"impose":[72],"exclusion":[73],"restrictions":[74],",":[75],"is,":[77],"model":[78],"specifications":[79],"certain":[82],"predict":[84],"but":[86,113],"have":[87],"no":[88],"effect":[89],"interest.":[94,171],"A":[95],"recent":[96],"proposal":[97],"employs":[98],"adaptive":[99,189],"LASSO":[100,190],"select":[102],"enter":[106],"into":[107],"equations,":[112],"its":[114],"performance":[115,175],"depends":[116],"so-called":[119],"covariance":[120],"assumption,":[121],"be":[124],"violated":[125],"small":[127],"moderate":[129],"samples.":[130],"To":[131],"address":[132],"these":[133],"challenges,":[134],"we":[135],"propose":[136],"two":[137,197],"families":[138],"spike-and-slab":[140],"priors":[141],"conduct":[143],"Bayesian":[144],"variable":[145],"sample":[148],"models.":[150],"These":[151],"prior":[152],"structures":[153],"allow":[154],"constructing":[156],"Gibbs":[158],"sampler":[159],"with":[160],"tractable":[161],"conditionals,":[162],"scalable":[165],"dimensions":[168],"We":[172,194],"illustrate":[173],"proposed":[178],"methodology":[179],"through":[180],"simulation":[182],"study":[183],"present":[185],"comparison":[187],"against":[188],"stepwise":[192],"selection.":[193],"also":[195],"provide":[196],"applications":[198],"using":[199],"publicly":[200],"available":[201],"real":[202],"data.":[203]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}
