{"id":"https://openalex.org/W3214524466","doi":"https://doi.org/10.1080/03610918.2023.2186334","title":"The expectation-maximization algorithm for autoregressive models with normal inverse Gaussian innovations","display_name":"The expectation-maximization algorithm for autoregressive models with normal inverse Gaussian innovations","publication_year":2023,"publication_date":"2023-03-13","ids":{"openalex":"https://openalex.org/W3214524466","doi":"https://doi.org/10.1080/03610918.2023.2186334","mag":"3214524466"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2023.2186334","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2186334","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/A5070889450","display_name":"Monika S. Dhull","orcid":"https://orcid.org/0000-0001-8807-0748"},"institutions":[{"id":"https://openalex.org/I119241673","display_name":"Indian Institute of Technology Ropar","ror":"https://ror.org/02qkhhn56","country_code":"IN","type":"education","lineage":["https://openalex.org/I119241673"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Monika S. Dhull","raw_affiliation_strings":["Department of Mathematics, Indian Institute of Technology Ropar, Rupnagar, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Indian Institute of Technology Ropar, Rupnagar, India","institution_ids":["https://openalex.org/I119241673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075289857","display_name":"Arun Kumar","orcid":"https://orcid.org/0000-0002-0460-5467"},"institutions":[{"id":"https://openalex.org/I119241673","display_name":"Indian Institute of Technology Ropar","ror":"https://ror.org/02qkhhn56","country_code":"IN","type":"education","lineage":["https://openalex.org/I119241673"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Kumar","raw_affiliation_strings":["Department of Mathematics, Indian Institute of Technology Ropar, Rupnagar, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Indian Institute of Technology Ropar, Rupnagar, India","institution_ids":["https://openalex.org/I119241673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073892482","display_name":"Agnieszka Wy\u0142oma\u0144ska","orcid":"https://orcid.org/0000-0001-9750-1351"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]},{"id":"https://openalex.org/I11923345","display_name":"Wroc\u0142aw University of Science and Technology","ror":"https://ror.org/008fyn775","country_code":"PL","type":"education","lineage":["https://openalex.org/I11923345"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Agnieszka Wy\u0142oma\u0144ska","raw_affiliation_strings":["Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wroclaw University of Science and Technology, Wroclaw, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wroclaw University of Science and Technology, Wroclaw, Poland","institution_ids":["https://openalex.org/I11923345","https://openalex.org/I686019"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070889450"],"corresponding_institution_ids":["https://openalex.org/I119241673"],"apc_list":null,"apc_paid":null,"fwci":0.296,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5311444,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"53","issue":"11","first_page":"5421","last_page":"5441"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9987000226974487,"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":0.9987000226974487,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.735394299030304},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6912983655929565},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46454739570617676},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.42293262481689453},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3960857391357422},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3844110369682312},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3777415156364441},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3689573109149933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3552502393722534},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32941198348999023},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2881624102592468}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.735394299030304},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6912983655929565},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46454739570617676},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.42293262481689453},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3960857391357422},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3844110369682312},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3777415156364441},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3689573109149933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3552502393722534},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32941198348999023},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2881624102592468},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2023.2186334","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2186334","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":67,"referenced_works":["https://openalex.org/W191692956","https://openalex.org/W623556437","https://openalex.org/W1486650488","https://openalex.org/W1487998535","https://openalex.org/W1548669759","https://openalex.org/W1567134758","https://openalex.org/W1596086225","https://openalex.org/W1930734808","https://openalex.org/W1967639437","https://openalex.org/W1973195653","https://openalex.org/W1975994995","https://openalex.org/W1976062144","https://openalex.org/W1976728325","https://openalex.org/W1984120483","https://openalex.org/W1988615517","https://openalex.org/W1996697006","https://openalex.org/W2004152321","https://openalex.org/W2009736376","https://openalex.org/W2018450048","https://openalex.org/W2022270721","https://openalex.org/W2024726293","https://openalex.org/W2027951671","https://openalex.org/W2029217165","https://openalex.org/W2033280533","https://openalex.org/W2037248439","https://openalex.org/W2049633694","https://openalex.org/W2052496848","https://openalex.org/W2063663311","https://openalex.org/W2079732597","https://openalex.org/W2086358052","https://openalex.org/W2089587982","https://openalex.org/W2096018560","https://openalex.org/W2099121102","https://openalex.org/W2117853077","https://openalex.org/W2118143383","https://openalex.org/W2123446302","https://openalex.org/W2130618320","https://openalex.org/W2152828142","https://openalex.org/W2161804347","https://openalex.org/W2164378403","https://openalex.org/W2166481425","https://openalex.org/W2293936600","https://openalex.org/W2299990237","https://openalex.org/W2317477318","https://openalex.org/W2325953669","https://openalex.org/W2410613289","https://openalex.org/W2512375057","https://openalex.org/W2518845577","https://openalex.org/W2574247507","https://openalex.org/W2592505882","https://openalex.org/W2798056406","https://openalex.org/W2885297711","https://openalex.org/W2901775251","https://openalex.org/W2992736482","https://openalex.org/W3104797951","https://openalex.org/W3124697023","https://openalex.org/W3127825417","https://openalex.org/W3139335947","https://openalex.org/W3141915193","https://openalex.org/W3171461985","https://openalex.org/W3198179977","https://openalex.org/W4232023503","https://openalex.org/W4234044903","https://openalex.org/W4245248307","https://openalex.org/W4255375128","https://openalex.org/W4292081177","https://openalex.org/W4300168003"],"related_works":["https://openalex.org/W2171218219","https://openalex.org/W1972271943","https://openalex.org/W2150410159","https://openalex.org/W3150905897","https://openalex.org/W4327525404","https://openalex.org/W4287185323","https://openalex.org/W1520183331","https://openalex.org/W2099889858","https://openalex.org/W2168175994","https://openalex.org/W2156628102"],"abstract_inverted_index":{"In":[0,93],"this":[1],"paper,":[2],"we":[3],"study":[4,67],"the":[5,26,31,41,44,51,57,71,96,118,124],"autoregressive":[6],"(AR)":[7],"model":[8,90,120,140],"with":[9,86,141,150],"normal":[10],"inverse":[11],"Gaussian":[12],"(NIG)":[13],"innovations.":[14],"The":[15,33,48,114,135],"NIG":[16,102,142],"distribution":[17,103],"is":[18,22,37,54,68,144],"semi":[19],"heavy-tailed":[20],"and":[21,62,80,107,130],"helpful":[23],"in":[24,30],"capturing":[25],"extreme":[27,151],"observations":[28],"present":[29],"data.":[32,134,159],"expectation-maximization":[34],"(EM)":[35],"algorithm":[36,106],"used":[38],"to":[39],"estimate":[40],"parameters":[42],"of":[43,50,101,117],"considered":[45],"AR(p)":[46],"model.":[47],"efficacy":[49],"estimation":[52,73,99],"procedure":[53],"shown":[55],"on":[56,123],"simulated":[58],"data":[59,129,149],"for":[60,89,147,156],"AR(2)":[61],"AR(1)":[63,139],"models.":[64],"A":[65],"comparative":[66],"presented,":[69],"where":[70],"classical":[72],"algorithms":[74],"are":[75,111,121],"also":[76,112],"incorporated,":[77],"namely,":[78],"Yule-Walker":[79],"conditional":[81],"least":[82],"squares":[83],"methods":[84],"along":[85],"EM":[87,105],"method":[88,110],"parameter":[91],"estimation.":[92],"simulation":[94],"study,":[95],"maximum":[97],"likelihood":[98],"(MLE)":[100],"by":[104],"iterative":[108],"Newton-Raphson":[109],"compared.":[113],"real-life":[115],"applications":[116],"introduced":[119],"demonstrated":[122],"NASDAQ":[125],"stock":[126],"market":[127],"index":[128],"US":[131],"gasoline":[132,157],"price":[133,158],"studies":[136],"show":[137],"that":[138],"residuals":[143],"good":[145],"fit":[146],"financial":[148],"values":[152],"as":[153,155],"well":[154]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
