{"id":"https://openalex.org/W2005630497","doi":"https://doi.org/10.1145/2592254","title":"Approximate Inference for Observation-Driven Time Series Models with Intractable Likelihoods","display_name":"Approximate Inference for Observation-Driven Time Series Models with Intractable Likelihoods","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2005630497","doi":"https://doi.org/10.1145/2592254","mag":"2005630497"},"language":"en","primary_location":{"id":"doi:10.1145/2592254","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2592254","pdf_url":null,"source":{"id":"https://openalex.org/S38703467","display_name":"ACM Transactions on Modeling and Computer Simulation","issn_l":"1049-3301","issn":["1049-3301","1558-1195"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Modeling and Computer Simulation","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/A5047259277","display_name":"Ajay Jasra","orcid":"https://orcid.org/0000-0003-4808-9131"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Ajay Jasra","raw_affiliation_strings":["National University of Singapore, Republic of Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Republic of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031347000","display_name":"Nikolas Kantas","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nikolas Kantas","raw_affiliation_strings":["Imperial College London, London, UK","#N#Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"#N#Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060194094","display_name":"Elena Ehrlich","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Elena Ehrlich","raw_affiliation_strings":["Imperial College London, London, UK","#N#Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"#N#Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047259277"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":2.93,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.9103629,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"24","issue":"3","first_page":"1","last_page":"25"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9962000250816345,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7463508248329163},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.7088446021080017},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.5516595840454102},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5372329354286194},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5223556756973267},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5173754096031189},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.48938435316085815},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48516350984573364},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45332425832748413},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4499342739582062},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.4475390613079071},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.44372448325157166},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.4309133291244507},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.43058687448501587},{"id":"https://openalex.org/keywords/exponential-random-graph-models","display_name":"Exponential random graph models","score":0.4300515055656433},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.41027072072029114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39184197783470154},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37940308451652527},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3789922595024109},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.30295872688293457},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23645615577697754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17861437797546387}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7463508248329163},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.7088446021080017},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.5516595840454102},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5372329354286194},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5223556756973267},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5173754096031189},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.48938435316085815},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48516350984573364},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45332425832748413},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4499342739582062},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.4475390613079071},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.44372448325157166},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.4309133291244507},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.43058687448501587},{"id":"https://openalex.org/C30549945","wikidata":"https://www.wikidata.org/wiki/Q5421526","display_name":"Exponential random graph models","level":4,"score":0.4300515055656433},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.41027072072029114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39184197783470154},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37940308451652527},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3789922595024109},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.30295872688293457},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23645615577697754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17861437797546387},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2592254","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2592254","pdf_url":null,"source":{"id":"https://openalex.org/S38703467","display_name":"ACM Transactions on Modeling and Computer Simulation","issn_l":"1049-3301","issn":["1049-3301","1558-1195"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Modeling and Computer Simulation","raw_type":"journal-article"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/40829","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/40829","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8833288592","display_name":null,"funder_award_id":"EP/J01365X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320320283","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10"},{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"},{"id":"https://openalex.org/F4320321026","display_name":"Ministry of Earth Sciences","ror":"https://ror.org/013cf5k59"},{"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":25,"referenced_works":["https://openalex.org/W1501586228","https://openalex.org/W1594863551","https://openalex.org/W1624586190","https://openalex.org/W1830883013","https://openalex.org/W1882169997","https://openalex.org/W1883186006","https://openalex.org/W2002479933","https://openalex.org/W2036050356","https://openalex.org/W2045345437","https://openalex.org/W2045973738","https://openalex.org/W2053332694","https://openalex.org/W2067392831","https://openalex.org/W2076197111","https://openalex.org/W2091860746","https://openalex.org/W2123726866","https://openalex.org/W2125979918","https://openalex.org/W2127079034","https://openalex.org/W2128306087","https://openalex.org/W2135267747","https://openalex.org/W2139812092","https://openalex.org/W2141800329","https://openalex.org/W2169737619","https://openalex.org/W3098713583","https://openalex.org/W4250389103","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2356093187","https://openalex.org/W164417758","https://openalex.org/W2032616735","https://openalex.org/W2186819079","https://openalex.org/W75953361","https://openalex.org/W4287728430","https://openalex.org/W2124138033","https://openalex.org/W4300007406","https://openalex.org/W2950346508","https://openalex.org/W4302398023"],"abstract_inverted_index":{"In":[0,137],"this":[1],"article,":[2],"we":[3,81],"consider":[4],"approximate":[5],"Bayesian":[6,75],"parameter":[7,52,221],"inference":[8,222],"for":[9,143,200,220],"observation-driven":[10],"time":[11,94],"series":[12],"models.":[13],"Such":[14],"statistical":[15,49,141],"models":[16,224],"appear":[17],"in":[18,42,161,225],"a":[19,69,102,120,173,187],"wide":[20],"variety":[21],"of":[22,92,108,186],"applications,":[23],"including":[24,51],"econometrics":[25],"and":[26,163,175],"applied":[27],"mathematics.":[28],"This":[29],"article":[30],"considers":[31],"the":[32,35,90,93,96,109,116,126,132,144,197],"scenario":[33],"where":[34],"likelihood":[36],"function":[37],"cannot":[38,46],"be":[39,206],"evaluated":[40],"pointwise;":[41],"such":[43,60],"cases,":[44],"one":[45],"perform":[47],"exact":[48,184],"inference,":[50,142],"estimation,":[53],"which":[54,124,179],"often":[55,113],"requires":[56],"advanced":[57,166],"computational":[58],"algorithms,":[59],"as":[61,84],"Markov":[62],"Chain":[63],"Monte":[64],"Carlo":[65],"(MCMC).":[66],"We":[67,171,214],"introduce":[68],"new":[70,174,217],"approximation":[71,146,185],"based":[72,181],"upon":[73,182],"Approximate":[74],"Computation":[76],"(ABC).":[77],"Under":[78],"some":[79],"conditions,":[80],"show":[82],"that":[83,111,155],"n":[85,89,162,209],"\u2192":[86],"\u221e,":[87],"with":[88],"length":[91],"series,":[95],"ABC":[97,122,145],"posterior":[98],"has,":[99],"almost":[100,135],"surely,":[101],"Maximum":[103],"A":[104],"Posteriori":[105],"(MAP)":[106],"estimator":[107],"parameters":[110],"is":[112,180,194,203],"different":[114],"from":[115,223],"true":[117,133],"parameter.":[118],"However,":[119],"noisy":[121],"MAP,":[123],"perturbs":[125],"original":[127],"data,":[128],"asymptotically":[129],"converges":[130],"to":[131,139,205],"parameter,":[134],"surely.":[136],"order":[138],"draw":[140],"adopted,":[147],"standard":[148],"MCMC":[149,177,218],"algorithms":[150,167],"can":[151,168],"have":[152],"acceptance":[153],"probabilities":[154],"fall":[156],"at":[157],"an":[158,183],"exponential":[159],"rate":[160],"slightly":[164],"more":[165],"mix":[169],"poorly.":[170],"develop":[172],"improved":[176],"kernel,":[178],"marginal":[188],"algorithm,":[189],"whose":[190],"cost":[191],"per":[192,212],"iteration":[193],"random,":[195],"but":[196],"expected":[198],"cost,":[199],"good":[201],"performance,":[202],"shown":[204],"O":[207],"(":[208],"2":[210],")":[211],"iteration.":[213],"implement":[215],"our":[216],"kernel":[219],"econometrics.":[226]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}