{"id":"https://openalex.org/W3003757530","doi":"https://doi.org/10.1080/03610918.2020.1720733","title":"Numerical characteristics and parameter estimation of finite mixed generalized normal distribution","display_name":"Numerical characteristics and parameter estimation of finite mixed generalized normal distribution","publication_year":2020,"publication_date":"2020-01-31","ids":{"openalex":"https://openalex.org/W3003757530","doi":"https://doi.org/10.1080/03610918.2020.1720733","mag":"3003757530"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2020.1720733","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1720733","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/A5100549335","display_name":"Luliang Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I14894300","display_name":"Foshan University","ror":"https://ror.org/02xvvvp28","country_code":"CN","type":"education","lineage":["https://openalex.org/I14894300"]},{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luliang Wen","raw_affiliation_strings":["Department of Mathematics, Foshan University, Foshan, P.R. China","Department of Statistics, Jinan University, Guangzhou, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Foshan University, Foshan, P.R. China","institution_ids":["https://openalex.org/I14894300"]},{"raw_affiliation_string":"Department of Statistics, Jinan University, Guangzhou, P.R. China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006214591","display_name":"Yanjun Qiu","orcid":"https://orcid.org/0000-0002-2250-5363"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjun Qiu","raw_affiliation_strings":["Department of Statistics, Jinan University, Guangzhou, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Jinan University, Guangzhou, P.R. China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376914","display_name":"Ming-hui Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]},{"id":"https://openalex.org/I3130751423","display_name":"Shaoguan University","ror":"https://ror.org/0286g6711","country_code":"CN","type":"education","lineage":["https://openalex.org/I3130751423"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Minghui Wang","raw_affiliation_strings":["Department of Statistics, Jinan University, Guangzhou, P.R. China","Department of Statistics, Shaoguan University, Shaoguan, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Jinan University, Guangzhou, P.R. China","institution_ids":["https://openalex.org/I159948400"]},{"raw_affiliation_string":"Department of Statistics, Shaoguan University, Shaoguan, P.R. China","institution_ids":["https://openalex.org/I3130751423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056102926","display_name":"Juliang Yin","orcid":"https://orcid.org/0000-0001-5097-9497"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Juliang Yin","raw_affiliation_strings":["Department of Statistics, Guangzhou University, Guangzhou, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Guangzhou University, Guangzhou, P.R. China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012491543","display_name":"Pingyan Chen","orcid":"https://orcid.org/0000-0002-3747-8003"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pingyan Chen","raw_affiliation_strings":["Department of Mathematics, Jinan University, Guangzhou, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Jinan University, Guangzhou, P.R. China","institution_ids":["https://openalex.org/I159948400"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012491543","https://openalex.org/A5056102926","https://openalex.org/A5100376914"],"corresponding_institution_ids":["https://openalex.org/I159948400","https://openalex.org/I3130751423","https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.8551,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.73714378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"51","issue":"7","first_page":"3596","last_page":"3620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9997000098228455,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9997000098228455,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9973999857902527,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9900000095367432,"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/kurtosis","display_name":"Kurtosis","score":0.8701112270355225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.741791844367981},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.5943813323974609},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.5894696712493896},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5515730381011963},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.4838391840457916},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.479838103055954},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.4657730758190155},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4566747844219208},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.31318649649620056},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.24939244985580444}],"concepts":[{"id":"https://openalex.org/C166963901","wikidata":"https://www.wikidata.org/wiki/Q287251","display_name":"Kurtosis","level":2,"score":0.8701112270355225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.741791844367981},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.5943813323974609},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.5894696712493896},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5515730381011963},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.4838391840457916},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.479838103055954},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.4657730758190155},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4566747844219208},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.31318649649620056},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.24939244985580444}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2020.1720733","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1720733","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":[{"id":"https://openalex.org/G4282516648","display_name":null,"funder_award_id":"61573006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1482072896","https://openalex.org/W1964746278","https://openalex.org/W1967460951","https://openalex.org/W1967639437","https://openalex.org/W1981359679","https://openalex.org/W2019470420","https://openalex.org/W2022852240","https://openalex.org/W2031426550","https://openalex.org/W2037823779","https://openalex.org/W2038014404","https://openalex.org/W2042513913","https://openalex.org/W2043967437","https://openalex.org/W2044579390","https://openalex.org/W2049633694","https://openalex.org/W2057272996","https://openalex.org/W2058515446","https://openalex.org/W2071897145","https://openalex.org/W2072009271","https://openalex.org/W2094007622","https://openalex.org/W2104985496","https://openalex.org/W2134218892","https://openalex.org/W2141637993","https://openalex.org/W2152922857","https://openalex.org/W2338509365","https://openalex.org/W2489540272","https://openalex.org/W2547713311","https://openalex.org/W2585418300","https://openalex.org/W2769489398","https://openalex.org/W2899629000","https://openalex.org/W4230835027"],"related_works":["https://openalex.org/W4225568567","https://openalex.org/W4286378979","https://openalex.org/W1496883226","https://openalex.org/W4297337052","https://openalex.org/W2028605949","https://openalex.org/W2282665605","https://openalex.org/W3216026256","https://openalex.org/W3129919015","https://openalex.org/W4390742338","https://openalex.org/W2037499216"],"abstract_inverted_index":{"In":[0,36],"this":[1],"paper,":[2],"a":[3,29,40,95],"univariate":[4],"finite":[5],"mixed":[6],"generalized":[7,33,128],"normal":[8,34,129,136],"distribution":[9],"(MixGND)":[10],"is":[11,85],"proposed.":[12],"First,":[13],"we":[14,38,119],"derive":[15],"some":[16],"probabilistic":[17],"properties":[18],"including":[19],"hazard":[20],"rate":[21],"function,":[22,24],"characteristic":[23],"kurtosis":[25,54],"and":[26,43,53,62,89,102,112,131,150],"skewness,":[27],"for":[28],"mixture":[30,125,133],"of":[31,51,66,94,108,126,134,153],"two":[32,127,135],"distributions.":[35,137],"particular,":[37],"use":[39,72],"geometric":[41],"analysis":[42,140],"numerical":[44],"simulation":[45],"technique":[46],"to":[47,87],"study":[48],"the":[49,73,99,109,124,132,144,148,154],"monotonicity":[50],"skewness":[52],"from":[55],"prescribing":[56],"corresponding":[57],"parameters.":[58],"Then":[59],"moment":[60],"estimation":[61,65,76],"maximum":[63,74],"likelihood":[64,75],"parameters":[67,93],"are":[68],"also":[69],"given.":[70],"To":[71],"(MLE)":[77],"method,":[78],"an":[79],"expectation":[80],"conditional":[81],"maximization":[82],"(ECM)":[83],"algorithm":[84],"proposed":[86],"estimate":[88],"numerically":[90],"simulate":[91],"seven":[92],"two-component":[96],"MixGND":[97],"under":[98],"same":[100],"variance":[101],"heteroscedasticity.":[103],"By":[104],"using":[105],"data":[106],"sets":[107],"S&P":[110],"500":[111],"Shanghai":[113],"Stock":[114],"Exchange":[115],"Composite":[116],"Index":[117],"(SSEC),":[118],"compare":[120],"goodness-of-fit":[121],"performance":[122],"between":[123],"distributions":[130],"The":[138],"empirical":[139],"results":[141],"show":[142],"that":[143],"former":[145],"better":[146],"describes":[147],"heavy-tailed":[149],"leptokurtic":[151],"characteristics":[152],"daily":[155],"returns.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}