{"id":"https://openalex.org/W4226211544","doi":"https://doi.org/10.1080/03610918.2022.2057543","title":"A Bayesian paradigm in a large class of L\u00e9vy-driven CARMA models for high frequency data","display_name":"A Bayesian paradigm in a large class of L\u00e9vy-driven CARMA models for high frequency data","publication_year":2022,"publication_date":"2022-04-04","ids":{"openalex":"https://openalex.org/W4226211544","doi":"https://doi.org/10.1080/03610918.2022.2057543"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2057543","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2057543","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","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/A5103126714","display_name":"Ali Asghar Sharifi","orcid":"https://orcid.org/0000-0003-1181-6032"},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ali Sharifi","raw_affiliation_strings":["Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040331634","display_name":"Ali Reza Taheriyoun","orcid":"https://orcid.org/0000-0002-2282-7741"},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ali R. Taheriyoun","raw_affiliation_strings":["Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057332656","display_name":"Hamideh D. Hamedani","orcid":null},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hamideh D. Hamedani","raw_affiliation_strings":["Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040331634"],"corresponding_institution_ids":["https://openalex.org/I48379061"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06275866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"53","issue":"4","first_page":"1824","last_page":"1836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10007","display_name":"Monetary Policy and Economic Impact","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2000","display_name":"General Economics, Econometrics and Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10067","display_name":"Stochastic processes and financial applications","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6691457033157349},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6672520637512207},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5911713242530823},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5763184428215027},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5230668187141418},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5151042342185974},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47275811433792114},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46002474427223206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43684467673301697},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.4210968017578125},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4139992594718933},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.31753355264663696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22408199310302734}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6691457033157349},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6672520637512207},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5911713242530823},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5763184428215027},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5230668187141418},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5151042342185974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47275811433792114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46002474427223206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43684467673301697},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.4210968017578125},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4139992594718933},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.31753355264663696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22408199310302734},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2057543","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2057543","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1520931194","https://openalex.org/W1587983714","https://openalex.org/W1993526900","https://openalex.org/W1994970668","https://openalex.org/W2041874997","https://openalex.org/W2050488482","https://openalex.org/W2052807037","https://openalex.org/W2055768229","https://openalex.org/W2077791698","https://openalex.org/W2123446302","https://openalex.org/W2158120228","https://openalex.org/W2171440547","https://openalex.org/W2202747776","https://openalex.org/W2471980104","https://openalex.org/W2979111378","https://openalex.org/W4231057775","https://openalex.org/W6720809420","https://openalex.org/W6750254569","https://openalex.org/W7062439954"],"related_works":["https://openalex.org/W2343819364","https://openalex.org/W2133205540","https://openalex.org/W2046798682","https://openalex.org/W2562263695","https://openalex.org/W2015518264","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W1718066205"],"abstract_inverted_index":{"Continuous-time":[0],"time":[1],"series":[2],"are":[3,81,108,117,132],"widely":[4],"used":[5],"for":[6,91,120],"modeling":[7],"the":[8,25,34,52,58,61,71,78,121,129,144],"realizations":[9,35],"of":[10,24,36,63,95,106,128,146,153],"those":[11],"phenomena":[12],"where":[13],"it":[14],"is":[15,68,89],"theoretically":[16],"possible":[17],"to":[18,32,56,135],"have":[19],"observation":[20],"at":[21],"any":[22],"point":[23],"sampling":[26],"domain.":[27],"However,":[28],"technical":[29],"restrictions":[30],"cause":[31],"see":[33],"such":[37],"processes":[38],"as":[39,157],"discrete-time":[40],"sample":[41],"paths.":[42],"We":[43,83,141],"project":[44],"time-domain":[45],"observations":[46],"into":[47],"frequency-domain":[48],"periodograms":[49],"and":[50,74,115],"employ":[51],"Whittle\u2019s":[53],"likelihood":[54],"approximation":[55],"make":[57],"inference":[59,67],"about":[60,77],"parameters":[62,107],"CARMA":[64],"processes.":[65],"The":[66,103,124],"given":[69],"under":[70,99],"Bayesian":[72],"paradigm":[73],"some":[75,100],"scenarios":[76],"prior":[79],"distributions":[80],"discussed.":[82],"show":[84],"that":[85],"our":[86],"proposed":[87],"estimator":[88],"robust":[90],"a":[92,111,158],"large":[93],"family":[94],"L\u00e9vy-driven":[96],"distributed":[97],"noises":[98],"mild":[101],"conditions.":[102],"Bayes":[104,148],"estimates":[105,131],"obtained":[109],"using":[110],"fast":[112],"MCMC":[113],"algorithm":[114],"they":[116],"examined":[118],"numerically":[119],"non-informative":[122],"priors.":[123],"mean":[125],"squared":[126],"errors":[127],"presented":[130],"also":[133,142],"compared":[134],"two":[136],"other":[137],"likelihood-based":[138],"estimators,":[139],"numerically.":[140],"examine":[143],"performance":[145],"this":[147],"estimate":[149],"in":[150],"prediction":[151],"procedure":[152],"exchange":[154],"rate":[155],"data":[156],"real":[159],"dataset.":[160]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
