{"id":"https://openalex.org/W4407909970","doi":"https://doi.org/10.1007/s11222-025-10584-z","title":"Simulation based composite likelihood","display_name":"Simulation based composite likelihood","publication_year":2025,"publication_date":"2025-02-25","ids":{"openalex":"https://openalex.org/W4407909970","doi":"https://doi.org/10.1007/s11222-025-10584-z","pmid":"https://pubmed.ncbi.nlm.nih.gov/40017662"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-025-10584-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-025-10584-z","pdf_url":null,"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","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s11222-025-10584-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008013779","display_name":"Lorenzo Rimella","orcid":"https://orcid.org/0000-0001-8846-1482"},"institutions":[{"id":"https://openalex.org/I1330701686","display_name":"Collegio Carlo Alberto","ror":"https://ror.org/0397knh37","country_code":"IT","type":"education","lineage":["https://openalex.org/I1330701686"]},{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Lorenzo Rimella","raw_affiliation_strings":["ESOMAS, University of Turin, Via Verdi 8, 10124 Turin, Italy","Statistics Initiative, Collegio Carlo Alberto, Piazza Arbarello 8, 10122 Turin, Italy","ESOMAS, University of Turin, Via Verdi 8, 10124, Turin, Italy","Statistics Initiative, Collegio Carlo Alberto, Piazza Arbarello 8, 10122, Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ESOMAS, University of Turin, Via Verdi 8, 10124 Turin, Italy","institution_ids":["https://openalex.org/I55143463"]},{"raw_affiliation_string":"Statistics Initiative, Collegio Carlo Alberto, Piazza Arbarello 8, 10122 Turin, Italy","institution_ids":["https://openalex.org/I1330701686"]},{"raw_affiliation_string":"ESOMAS, University of Turin, Via Verdi 8, 10124, Turin, Italy","institution_ids":["https://openalex.org/I55143463"]},{"raw_affiliation_string":"Statistics Initiative, Collegio Carlo Alberto, Piazza Arbarello 8, 10122, Turin, Italy","institution_ids":["https://openalex.org/I1330701686"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071700332","display_name":"Chris Jewell","orcid":"https://orcid.org/0000-0002-7902-2178"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chris Jewell","raw_affiliation_strings":["Mathematical Sciences, Lancaster University, Lancaster, LA14YF UK","Mathematical Sciences, Lancaster University, Lancaster, LA14YF, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematical Sciences, Lancaster University, Lancaster, LA14YF UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Mathematical Sciences, Lancaster University, Lancaster, LA14YF, UK","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085978090","display_name":"Paul Fearnhead","orcid":"https://orcid.org/0000-0002-9386-2341"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Paul Fearnhead","raw_affiliation_strings":["Mathematical Sciences, Lancaster University, Lancaster, LA14YF UK","Mathematical Sciences, Lancaster University, Lancaster, LA14YF, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematical Sciences, Lancaster University, Lancaster, LA14YF UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Mathematical Sciences, Lancaster University, Lancaster, LA14YF, UK","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008013779"],"corresponding_institution_ids":["https://openalex.org/I1330701686","https://openalex.org/I55143463"],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":{"value":2890,"currency":"USD","value_usd":2890},"fwci":2.59,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.87612846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"35","issue":"3","first_page":"58","last_page":"58"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.826200008392334,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.826200008392334,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.043299999088048935,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.024800000712275505,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5853259563446045},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5828917622566223},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.572072446346283},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5296494960784912},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.5029060244560242},{"id":"https://openalex.org/keywords/empirical-likelihood","display_name":"Empirical likelihood","score":0.4972892105579376},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4523412585258484},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.43689513206481934},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.42704248428344727},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4256255328655243},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3963923752307892},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3762401342391968},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.35559985041618347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3540244698524475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27872204780578613},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.25185734033584595}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5853259563446045},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5828917622566223},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.572072446346283},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5296494960784912},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.5029060244560242},{"id":"https://openalex.org/C2781117939","wikidata":"https://www.wikidata.org/wiki/Q5374245","display_name":"Empirical likelihood","level":3,"score":0.4972892105579376},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4523412585258484},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.43689513206481934},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.42704248428344727},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4256255328655243},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3963923752307892},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3762401342391968},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35559985041618347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3540244698524475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27872204780578613},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25185734033584595},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s11222-025-10584-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-025-10584-z","pdf_url":null,"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":"pmid:40017662","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40017662","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":"Statistics and computing","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11861035","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11861035","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11861035/pdf/11222_2025_Article_10584.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":"Stat Comput","raw_type":"Text"},{"id":"pmh:oai:aisberg.unibg.it:10446/305489","is_oa":true,"landing_page_url":"https://hdl.handle.net/10446/305489","pdf_url":null,"source":{"id":"https://openalex.org/S4377196347","display_name":"Aisberg (University of Bergamo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11039511","host_organization_name":"University of Bergamo","host_organization_lineage":["https://openalex.org/I11039511"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s11222-025-10584-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-025-10584-z","pdf_url":null,"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/G1579515842","display_name":null,"funder_award_id":"EP/R018561","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1974824942","display_name":null,"funder_award_id":"R018561","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3181550465","display_name":"ProbAI: A Hub for the Mathematical and Computational Foundations of Probabilistic AI","funder_award_id":"EP/Y028783/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3402893575","display_name":null,"funder_award_id":"EP/R018561/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4870096331","display_name":"New Approaches to Bayesian Data Science: Tackling Challenges from the Health Sciences","funder_award_id":"EP/R018561/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G6001630035","display_name":null,"funder_award_id":"EP/R018561/1","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"},{"id":"https://openalex.org/G6631254222","display_name":null,"funder_award_id":"Bayes4Health","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7356090129","display_name":null,"funder_award_id":"EP/Y028783/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G926698369","display_name":null,"funder_award_id":"R034710","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G965103402","display_name":"CoSInES (COmputational Statistical INference for Engineering and Security)","funder_award_id":"EP/R034710/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320324041","display_name":"Universit\u00e0 degli Studi di Torino","ror":"https://ror.org/048tbm396"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W10548402","https://openalex.org/W1514750300","https://openalex.org/W1539673959","https://openalex.org/W1594863551","https://openalex.org/W1822984620","https://openalex.org/W1994510541","https://openalex.org/W1995053220","https://openalex.org/W2005986688","https://openalex.org/W2007322170","https://openalex.org/W2036812059","https://openalex.org/W2058989213","https://openalex.org/W2119813768","https://openalex.org/W2153975459","https://openalex.org/W2161636141","https://openalex.org/W2162554556","https://openalex.org/W2166022262","https://openalex.org/W2914908364","https://openalex.org/W2925220679","https://openalex.org/W2963077819","https://openalex.org/W3090482648","https://openalex.org/W3100586012","https://openalex.org/W3104251110","https://openalex.org/W4205814206","https://openalex.org/W4206548271","https://openalex.org/W4292512692","https://openalex.org/W4323339087","https://openalex.org/W4382932107","https://openalex.org/W4383218616","https://openalex.org/W4401671849","https://openalex.org/W6630827713"],"related_works":["https://openalex.org/W2109606780","https://openalex.org/W1480082381","https://openalex.org/W4299976848","https://openalex.org/W2775602707","https://openalex.org/W308423894","https://openalex.org/W4297898818","https://openalex.org/W1436597729","https://openalex.org/W3021878258","https://openalex.org/W2254601135","https://openalex.org/W3020078843"],"abstract_inverted_index":{"Inference":[0],"for":[1],"high-dimensional":[2],"hidden":[3],"Markov":[4],"models":[5],"is":[6,92],"challenging":[7],"due":[8],"to":[9,58,73,94,99,107,130],"the":[10,16,39,42,68,82,85],"exponential-in-dimension":[11],"computational":[12],"cost":[13],"of":[14,44,84],"calculating":[15],"likelihood.":[17],"To":[18],"address":[19],"this":[20],"issue,":[21],"we":[22,37,48],"introduce":[23],"an":[24],"innovative":[25],"composite":[26],"likelihood":[27,40,78],"approach":[28],"called":[29],"\"Simulation":[30],"Based":[31],"Composite":[32],"Likelihood\"":[33],"(SimBa-CL).":[34],"With":[35],"SimBa-CL,":[36],"approximate":[38,59,109],"by":[41],"product":[43],"its":[45,123],"marginals,":[46],"which":[47,117],"estimate":[49],"using":[50],"Monte":[51],"Carlo":[52],"sampling.":[53],"In":[54],"a":[55,77],"similar":[56],"vein":[57],"Bayesian":[60],"computation":[61],"(ABC),":[62],"SimBa-CL":[63,129],"requires":[64],"multiple":[65],"simulations":[66],"from":[67],"model,":[69],"but,":[70],"in":[71],"contrast":[72],"ABC,":[74],"it":[75,91],"provides":[76],"approximation":[79],"that":[80],"guides":[81],"optimization":[83,104],"parameters.":[86],"Leveraging":[87],"automatic":[88],"differentiation":[89],"libraries,":[90],"simple":[93],"calculate":[95],"gradients":[96],"and":[97,121,127],"Hessians":[98],"not":[100],"only":[101],"speed":[102],"up":[103],"but":[105],"also":[106],"build":[108],"confidence":[110],"sets.":[111],"We":[112],"present":[113],"extensive":[114],"empirical":[115],"results":[116],"validate":[118],"our":[119],"theory":[120],"demonstrate":[122],"advantage":[124],"over":[125],"SMC,":[126],"apply":[128],"real-world":[131],"Aphtovirus":[132],"data.":[133],"Supplementary":[134],"Information:":[135],"The":[136],"online":[137],"version":[138],"contains":[139],"supplementary":[140],"material":[141],"available":[142],"at":[143],"10.1007/s11222-025-10584-z.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}