{"id":"https://openalex.org/W7126409009","doi":"https://doi.org/10.1007/s11222-026-10825-9","title":"Posterior SBC: simulation-based calibration checking conditional on data","display_name":"Posterior SBC: simulation-based calibration checking conditional on data","publication_year":2026,"publication_date":"2026-01-31","ids":{"openalex":"https://openalex.org/W7126409009","doi":"https://doi.org/10.1007/s11222-026-10825-9"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-026-10825-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-026-10825-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10825-9.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10825-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002531412","display_name":"Teemu S\u00e4ilynoja","orcid":"https://orcid.org/0000-0002-5249-348X"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Teemu S\u00e4ilynoja","raw_affiliation_strings":["Department of Computer Science, Aalto University, Espoo, Finland"],"raw_orcid":"https://orcid.org/0000-0002-5249-348X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aalto University, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032658236","display_name":"Marvin Schmitt","orcid":"https://orcid.org/0000-0002-7967-4723"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marvin Schmitt","raw_affiliation_strings":["Cluster of Excellence SimTech, University of Stuttgart, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0000-0002-7967-4723","affiliations":[{"raw_affiliation_string":"Cluster of Excellence SimTech, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124567429","display_name":"Paul-Christian B\u00fcrkner","orcid":null},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Paul-Christian B\u00fcrkner","raw_affiliation_strings":["Department of statistics, TU Dortmund University, Dortmund, Germany"],"raw_orcid":"https://orcid.org/0000-0001-5765-8995","affiliations":[{"raw_affiliation_string":"Department of statistics, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124596510","display_name":"Aki Vehtari","orcid":null},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Aki Vehtari","raw_affiliation_strings":["Department of Computer Science, Aalto University, Espoo, Finland"],"raw_orcid":"https://orcid.org/0000-0003-2164-9469","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aalto University, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002531412"],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1157754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.43299999833106995,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.43299999833106995,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11883","display_name":"Embodied and Extended Cognition","score":0.14810000360012054,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.04470000043511391,"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/inference","display_name":"Inference","score":0.8022000193595886},{"id":"https://openalex.org/keywords/fiducial-inference","display_name":"Fiducial inference","score":0.5978999733924866},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5964000225067139},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5019000172615051},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4684000015258789},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.4415000081062317},{"id":"https://openalex.org/keywords/predictive-inference","display_name":"Predictive inference","score":0.4223000109195709},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.413100004196167},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4007999897003174}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8022000193595886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6115999817848206},{"id":"https://openalex.org/C95167961","wikidata":"https://www.wikidata.org/wiki/Q4483495","display_name":"Fiducial inference","level":5,"score":0.5978999733924866},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5964000225067139},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5115000009536743},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4684000015258789},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.4415000081062317},{"id":"https://openalex.org/C917703","wikidata":"https://www.wikidata.org/wiki/Q7239668","display_name":"Predictive inference","level":5,"score":0.4223000109195709},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.413100004196167},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4007999897003174},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3919000029563904},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.35359999537467957},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.3409000039100647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33160001039505005},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3133000135421753},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.28130000829696655},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26100000739097595}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11222-026-10825-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-026-10825-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10825-9.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmh:oai:aaltodoc.aalto.fi:123456789/143182","is_oa":true,"landing_page_url":"https://research.aalto.fi/en/publications/21571ab8-ebe4-446c-b836-9db0a28364da","pdf_url":null,"source":{"id":"https://openalex.org/S4306401662","display_name":"Aaltodoc (Aalto University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I9927081","host_organization_name":"Aalto University","host_organization_lineage":["https://openalex.org/I9927081"],"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":null,"raw_type":"publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s11222-026-10825-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-026-10825-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10825-9.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1393714528","display_name":null,"funder_award_id":"520388526","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G1650656601","display_name":"Safe iterative Bayesian model building","funder_award_id":"340721","funder_id":"https://openalex.org/F4320321108","funder_display_name":"Academy of Finland"},{"id":"https://openalex.org/G3562914802","display_name":null,"funder_award_id":"101070617","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6251754251","display_name":null,"funder_award_id":"951847","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7428092924","display_name":null,"funder_award_id":"EXC-2075 - 390740016","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8606689470","display_name":null,"funder_award_id":"340721","funder_id":"https://openalex.org/F4320321108","funder_display_name":"Academy of Finland"},{"id":"https://openalex.org/G8784604414","display_name":null,"funder_award_id":"390740016","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"},{"id":"https://openalex.org/F4320321394","display_name":"Aalto-Yliopisto","ror":"https://ror.org/020hwjq30"},{"id":"https://openalex.org/F4320334747","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7126409009.pdf"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W32980360","https://openalex.org/W1526262927","https://openalex.org/W1997628954","https://openalex.org/W2027728102","https://openalex.org/W2040011853","https://openalex.org/W2045968318","https://openalex.org/W2053338030","https://openalex.org/W2071187610","https://openalex.org/W2129641119","https://openalex.org/W2290798512","https://openalex.org/W2747622113","https://openalex.org/W2753599755","https://openalex.org/W2754201019","https://openalex.org/W2791673449","https://openalex.org/W2915656168","https://openalex.org/W2920804790","https://openalex.org/W2953082877","https://openalex.org/W2962703949","https://openalex.org/W3012496101","https://openalex.org/W3035994216","https://openalex.org/W3137735170","https://openalex.org/W4220894006","https://openalex.org/W4248681815","https://openalex.org/W4362637639","https://openalex.org/W4386965882","https://openalex.org/W4388952075","https://openalex.org/W4391944190","https://openalex.org/W4392566137","https://openalex.org/W4404282898"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Simulation-based":[1],"calibration":[2],"checking":[3],"(SBC)":[4],"refers":[5],"to":[6,75,123],"the":[7,30,36,43,47,52,78,100,125,133],"validation":[8],"of":[9,85,135],"an":[10],"inference":[11,21,53,79,101,126,169],"algorithm":[12],"and":[13,32,45,70,116,156],"model":[14,38,149,162],"implementation":[15],"through":[16],"testing":[17,50],"self-consistency":[18],"with":[19,59,170],"repeated":[20],"on":[22,104,128],"data":[23,57,107],"simulated":[24,56],"from":[25,42],"a":[26,82,148,158],"generative":[27,37],"model.":[28],"In":[29,109],"original":[31],"commonly":[33],"used":[34,122],"approach,":[35],"uses":[39],"parameters":[40],"drawn":[41],"prior,":[44],"thus":[46],"approach":[48,67],"is":[49,68,151,164],"whether":[51,77,99],"works":[54,80,102],"for":[55,81],"generated":[58],"parameter":[60],"values":[61],"plausible":[62],"under":[63],"that":[64,105,150],"prior.":[65],"This":[66],"natural":[69],"desirable":[71],"when":[72],"we":[73,87,94,112],"want":[74],"test":[76],"wide":[83],"range":[84],"datasets":[86],"might":[88],"observe.":[89],"However,":[90],"after":[91],"observing":[92],"data,":[93],"are":[95],"interested":[96],"in":[97,138],"answering":[98],"conditional":[103],"particular":[106],".":[108],"this":[110],"paper,":[111],"propose":[113],"posterior":[114,136],"SBC":[115,137],"demonstrate":[117],"how":[118],"it":[119],"can":[120],"be":[121],"validate":[124],"conditionally":[127],"observed":[129],"data.":[130],"We":[131],"illustrate":[132],"utility":[134],"three":[139],"case":[140],"studies:":[141],"(1)":[142],"A":[143],"simple":[144],"multilevel":[145],"model;":[146],"(2)":[147],"governed":[152],"by":[153],"differential":[154],"equations;":[155],"(3)":[157],"joint":[159],"integrative":[160],"neuroscience":[161],"which":[163],"approximated":[165],"via":[166],"amortized":[167],"Bayesian":[168],"neural":[171],"networks.":[172]},"counts_by_year":[],"updated_date":"2026-06-20T22:02:38.213706","created_date":"2026-02-02T00:00:00"}