{"id":"https://openalex.org/W2508056651","doi":"https://doi.org/10.1080/03610918.2016.1212067","title":"Likelihood procedure for testing changes in skew normal model with applications to stock returns","display_name":"Likelihood procedure for testing changes in skew normal model with applications to stock returns","publication_year":2016,"publication_date":"2016-09-03","ids":{"openalex":"https://openalex.org/W2508056651","doi":"https://doi.org/10.1080/03610918.2016.1212067","mag":"2508056651"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2016.1212067","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2016.1212067","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/A5071391191","display_name":"Khamis K. Said","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Khamis K. Said","raw_affiliation_strings":["School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043980312","display_name":"Wei Ning","orcid":"https://orcid.org/0000-0002-2056-3236"},"institutions":[{"id":"https://openalex.org/I157417397","display_name":"Bowling Green State University","ror":"https://ror.org/00ay7va13","country_code":"US","type":"education","lineage":["https://openalex.org/I157417397"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wei Ning","raw_affiliation_strings":["Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, Ohio, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, Ohio, USA","institution_ids":["https://openalex.org/I157417397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027726845","display_name":"Yubin Tian","orcid":"https://orcid.org/0000-0002-3162-5738"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubin Tian","raw_affiliation_strings":["School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043980312"],"corresponding_institution_ids":["https://openalex.org/I157417397"],"apc_list":null,"apc_paid":null,"fwci":0.3624,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.690097,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"46","issue":"9","first_page":"6790","last_page":"6802"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9927999973297119,"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/T11886","display_name":"Agricultural risk and resilience","score":0.9401999711990356,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/skew-normal-distribution","display_name":"Skew normal distribution","score":0.8633875846862793},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.7931704521179199},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.639021635055542},{"id":"https://openalex.org/keywords/normal-family","display_name":"Normal family","score":0.5864867568016052},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5354215502738953},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.5259338021278381},{"id":"https://openalex.org/keywords/generalized-normal-distribution","display_name":"Generalized normal distribution","score":0.5040320754051208},{"id":"https://openalex.org/keywords/test-statistic","display_name":"Test statistic","score":0.5014641284942627},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4833938181400299},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4617372453212738},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42399269342422485},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4153476059436798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40209609270095825},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.36987972259521484},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3607872426509857},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11918249726295471},{"id":"https://openalex.org/keywords/normality","display_name":"Normality","score":0.09027859568595886},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07015058398246765}],"concepts":[{"id":"https://openalex.org/C43694697","wikidata":"https://www.wikidata.org/wiki/Q3258551","display_name":"Skew normal distribution","level":3,"score":0.8633875846862793},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.7931704521179199},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.639021635055542},{"id":"https://openalex.org/C173058130","wikidata":"https://www.wikidata.org/wiki/Q1049280","display_name":"Normal family","level":3,"score":0.5864867568016052},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5354215502738953},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5259338021278381},{"id":"https://openalex.org/C171383496","wikidata":"https://www.wikidata.org/wiki/Q2497477","display_name":"Generalized normal distribution","level":3,"score":0.5040320754051208},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.5014641284942627},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4833938181400299},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4617372453212738},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42399269342422485},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4153476059436798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40209609270095825},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.36987972259521484},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3607872426509857},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11918249726295471},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.09027859568595886},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07015058398246765},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/03610918.2016.1212067","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2016.1212067","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"},{"id":"pmh:oai:scholarworks.bgsu.edu:math_stat_pub-1069","is_oa":false,"landing_page_url":"https://scholarworks.bgsu.edu/math_stat_pub/70","pdf_url":null,"source":{"id":"https://openalex.org/S4306402596","display_name":"ScholarWorks@BGSU (Bowling Green State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157417397","host_organization_name":"Bowling Green State University","host_organization_lineage":["https://openalex.org/I157417397"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Mathematics and Statistics Faculty Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W94194614","https://openalex.org/W621293842","https://openalex.org/W639907764","https://openalex.org/W1577286032","https://openalex.org/W1971707571","https://openalex.org/W1982112356","https://openalex.org/W1985971417","https://openalex.org/W1992110458","https://openalex.org/W1992748910","https://openalex.org/W2001674776","https://openalex.org/W2002057006","https://openalex.org/W2019669268","https://openalex.org/W2025913337","https://openalex.org/W2031994746","https://openalex.org/W2034906135","https://openalex.org/W2040045248","https://openalex.org/W2049585131","https://openalex.org/W2051903196","https://openalex.org/W2073397946","https://openalex.org/W2080413358","https://openalex.org/W2092224475","https://openalex.org/W2095283167","https://openalex.org/W2116855184","https://openalex.org/W2136986719","https://openalex.org/W2152224043","https://openalex.org/W2171050536","https://openalex.org/W2796034401","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2183005240","https://openalex.org/W1981359679","https://openalex.org/W2419056419","https://openalex.org/W2460338119","https://openalex.org/W2912733426","https://openalex.org/W2952512382","https://openalex.org/W2081025540","https://openalex.org/W2508056651","https://openalex.org/W251522814","https://openalex.org/W2130221871"],"abstract_inverted_index":{"The":[0],"skew":[1,115,162],"normal":[2,19,66,116,163],"distribution":[3,8,20,42,95,117,164],"family":[4,9,43],"is":[5],"an":[6],"attractive":[7],"due":[10],"to":[11,93,107,134,143],"its":[12],"mathematical":[13],"tractability":[14],"and":[15,37,172],"inclusion":[16],"of":[17,61,70,88,113,123,138,152,160],"the":[18,22,65,76,86,102,111,114,124,136,139,149,153,161,177],"as":[21,34],"special":[23],"case.":[24],"It":[25],"has":[26,44,82],"wide":[27],"applications":[28],"in":[29,54,110,155,158],"many":[30],"applied":[31],"fields":[32],"such":[33],"finance,":[35],"economics,":[36],"medical":[38],"research.":[39],"Such":[40],"a":[41],"been":[45,83,129],"studied":[46],"extensively":[47],"since":[48],"it":[49],"was":[50],"introduced":[51],"by":[52],"Azzalini":[53],"1985":[55],"Azzalini,":[56],"A.":[57],"(1985).":[58],"A":[59],"class":[60],"distributions":[62],"which":[63],"includes":[64],"ones.":[67],"Scandinavian":[68],"Journal":[69],"Statistics":[71],"12:171\u2013178.":[72],"[Google":[73],"Scholar]":[74],"for":[75],"first":[77],"time.":[78],"Yet,":[79],"few":[80],"work":[81],"done":[84],"on":[85,167],"study":[87],"change":[89],"point":[90],"problem":[91],"related":[92],"this":[94,98],"family.":[96],"In":[97],"article,":[99],"we":[100],"propose":[101],"likelihood":[103],"ratio":[104],"test":[105,125],"(LRT)":[106],"detect":[108],"changes":[109,157],"parameters":[112,159],"associated":[118],"with":[119],"some":[120,144],"asymptotic":[121],"results":[122],"statistic.":[126],"Simulations":[127],"have":[128],"conducted":[130],"under":[131],"different":[132],"scenarios":[133],"investigate":[135],"performance":[137],"proposed":[140],"method.":[141],"Comparisons":[142],"other":[145],"existing":[146],"method":[147,154],"indicate":[148],"comparable":[150],"power":[151],"detecting":[156],"model.":[165],"Applications":[166],"two":[168],"real":[169],"data:":[170],"Brazilian":[171],"Tanzanian":[173],"stock":[174],"returns":[175],"illustrate":[176],"detection":[178],"procedure.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-29T09:21:14.243279","created_date":"2025-10-10T00:00:00"}
