{"id":"https://openalex.org/W4403976530","doi":"https://doi.org/10.3390/axioms13110749","title":"Maximum Penalized Likelihood Estimation of the Skew\u2013t Link Model for Binomial Response Data","display_name":"Maximum Penalized Likelihood Estimation of the Skew\u2013t Link Model for Binomial Response Data","publication_year":2024,"publication_date":"2024-10-30","ids":{"openalex":"https://openalex.org/W4403976530","doi":"https://doi.org/10.3390/axioms13110749"},"language":"en","primary_location":{"id":"doi:10.3390/axioms13110749","is_oa":true,"landing_page_url":"https://doi.org/10.3390/axioms13110749","pdf_url":"https://www.mdpi.com/2075-1680/13/11/749/pdf?version=1730359109","source":{"id":"https://openalex.org/S4210173132","display_name":"Axioms","issn_l":"2075-1680","issn":["2075-1680"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Axioms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2075-1680/13/11/749/pdf?version=1730359109","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069333941","display_name":"Omar Chocotea-Poca","orcid":"https://orcid.org/0000-0002-6490-7491"},"institutions":[{"id":"https://openalex.org/I10457146","display_name":"Universidad de Santiago de Chile","ror":"https://ror.org/02ma57s91","country_code":"CL","type":"education","lineage":["https://openalex.org/I10457146"]},{"id":"https://openalex.org/I4210086410","display_name":"Universidad Bernardo O'Higgins","ror":"https://ror.org/00x0xhn70","country_code":"CL","type":"education","lineage":["https://openalex.org/I4210086410"]},{"id":"https://openalex.org/I79274474","display_name":"University of Valpara\u00edso","ror":"https://ror.org/00h9jrb69","country_code":"CL","type":"education","lineage":["https://openalex.org/I79274474"]}],"countries":["CL"],"is_corresponding":true,"raw_author_name":"Omar Chocotea-Poca","raw_affiliation_strings":["Department of Mathematics and Computer Science, Universidad de Santiago de Chile, Avenida Libertador Bernardo O\u2019Higgins 3363, Santiago 9170022, Chile","Statistical Institute, Universidad de Valpara\u00edso, Avenida Gran Breta\u00f1a 1111, Valpara\u00edso 2360102, Chile","Department of Mathematics and Computer Science, Universidad de Santiago de Chile, Avenida Libertador Bernardo O'Higgins 3363, Santiago 9170022, Chile"],"raw_orcid":"https://orcid.org/0000-0002-6490-7491","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Universidad de Santiago de Chile, Avenida Libertador Bernardo O\u2019Higgins 3363, Santiago 9170022, Chile","institution_ids":["https://openalex.org/I4210086410","https://openalex.org/I10457146"]},{"raw_affiliation_string":"Statistical Institute, Universidad de Valpara\u00edso, Avenida Gran Breta\u00f1a 1111, Valpara\u00edso 2360102, Chile","institution_ids":["https://openalex.org/I79274474"]},{"raw_affiliation_string":"Department of Mathematics and Computer Science, Universidad de Santiago de Chile, Avenida Libertador Bernardo O'Higgins 3363, Santiago 9170022, Chile","institution_ids":["https://openalex.org/I4210086410","https://openalex.org/I10457146"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030296026","display_name":"Orietta Nicolis","orcid":"https://orcid.org/0000-0001-8046-6983"},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":true,"raw_author_name":"Orietta Nicolis","raw_affiliation_strings":["Engineering Faculty, Universidad Andres Bello, Calle Quillota 980, Vi\u00f1a del Mar 2520000, Chile"],"raw_orcid":"https://orcid.org/0000-0001-8046-6983","affiliations":[{"raw_affiliation_string":"Engineering Faculty, Universidad Andres Bello, Calle Quillota 980, Vi\u00f1a del Mar 2520000, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086835079","display_name":"Germ\u00e1n Ibacache\u2010Pulgar","orcid":null},"institutions":[{"id":"https://openalex.org/I79274474","display_name":"University of Valpara\u00edso","ror":"https://ror.org/00h9jrb69","country_code":"CL","type":"education","lineage":["https://openalex.org/I79274474"]}],"countries":["CL"],"is_corresponding":true,"raw_author_name":"Germ\u00e1n Ibacache-Pulgar","raw_affiliation_strings":["Centro de Estudios Atmosf\u00e9ricos y Cambio Clim\u00e1tico, Universidad de Valpara\u00edso, Avenida Gran Breta\u00f1a 644, Valpara\u00edso 2360102, Chile","Statistical Institute, Universidad de Valpara\u00edso, Avenida Gran Breta\u00f1a 1111, Valpara\u00edso 2360102, Chile"],"raw_orcid":"https://orcid.org/0000-0002-6038-2149","affiliations":[{"raw_affiliation_string":"Centro de Estudios Atmosf\u00e9ricos y Cambio Clim\u00e1tico, Universidad de Valpara\u00edso, Avenida Gran Breta\u00f1a 644, Valpara\u00edso 2360102, Chile","institution_ids":["https://openalex.org/I79274474"]},{"raw_affiliation_string":"Statistical Institute, Universidad de Valpara\u00edso, Avenida Gran Breta\u00f1a 1111, Valpara\u00edso 2360102, Chile","institution_ids":["https://openalex.org/I79274474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030296026","https://openalex.org/A5069333941","https://openalex.org/A5086835079"],"corresponding_institution_ids":["https://openalex.org/I10457146","https://openalex.org/I13897259","https://openalex.org/I4210086410","https://openalex.org/I79274474"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.6243,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73607283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"13","issue":"11","first_page":"749","last_page":"749"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9951000213623047,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9951000213623047,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9929999709129333,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9886000156402588,"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/skew","display_name":"Skew","score":0.7708662748336792},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.7265434265136719},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.6977298259735107},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5998892188072205},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5881181955337524},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.5664361715316772},{"id":"https://openalex.org/keywords/quasi-likelihood","display_name":"Quasi-likelihood","score":0.543945848941803},{"id":"https://openalex.org/keywords/binomial","display_name":"Binomial (polynomial)","score":0.5173211097717285},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4493839144706726},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.431530624628067},{"id":"https://openalex.org/keywords/binomial-distribution","display_name":"Binomial distribution","score":0.4259442687034607},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32781875133514404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3173316717147827},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1110025942325592},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.07426482439041138}],"concepts":[{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.7708662748336792},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.7265434265136719},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.6977298259735107},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5998892188072205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5881181955337524},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.5664361715316772},{"id":"https://openalex.org/C91025261","wikidata":"https://www.wikidata.org/wiki/Q7269460","display_name":"Quasi-likelihood","level":4,"score":0.543945848941803},{"id":"https://openalex.org/C2781315470","wikidata":"https://www.wikidata.org/wiki/Q193623","display_name":"Binomial (polynomial)","level":2,"score":0.5173211097717285},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4493839144706726},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.431530624628067},{"id":"https://openalex.org/C41054675","wikidata":"https://www.wikidata.org/wiki/Q185547","display_name":"Binomial distribution","level":2,"score":0.4259442687034607},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32781875133514404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3173316717147827},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1110025942325592},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.07426482439041138},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/axioms13110749","is_oa":true,"landing_page_url":"https://doi.org/10.3390/axioms13110749","pdf_url":"https://www.mdpi.com/2075-1680/13/11/749/pdf?version=1730359109","source":{"id":"https://openalex.org/S4210173132","display_name":"Axioms","issn_l":"2075-1680","issn":["2075-1680"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Axioms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6d566365296b463d898a950a2da18a47","is_oa":false,"landing_page_url":"https://doaj.org/article/6d566365296b463d898a950a2da18a47","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Axioms, Vol 13, Iss 11, p 749 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/axioms13110749","is_oa":true,"landing_page_url":"https://doi.org/10.3390/axioms13110749","pdf_url":"https://www.mdpi.com/2075-1680/13/11/749/pdf?version=1730359109","source":{"id":"https://openalex.org/S4210173132","display_name":"Axioms","issn_l":"2075-1680","issn":["2075-1680"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Axioms","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality"},{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403976530.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W94194614","https://openalex.org/W110959178","https://openalex.org/W160785014","https://openalex.org/W747911303","https://openalex.org/W1572039738","https://openalex.org/W1967396544","https://openalex.org/W1976031668","https://openalex.org/W1980071153","https://openalex.org/W1982914322","https://openalex.org/W1999298891","https://openalex.org/W2012328620","https://openalex.org/W2012500654","https://openalex.org/W2017034551","https://openalex.org/W2023219679","https://openalex.org/W2030757251","https://openalex.org/W2033076513","https://openalex.org/W2041933477","https://openalex.org/W2054336336","https://openalex.org/W2090909148","https://openalex.org/W2149783974","https://openalex.org/W2735405873","https://openalex.org/W2801490189","https://openalex.org/W2920927167","https://openalex.org/W2963369138","https://openalex.org/W3111543990","https://openalex.org/W6603863532","https://openalex.org/W6606539394"],"related_works":["https://openalex.org/W2189104843","https://openalex.org/W2338849605","https://openalex.org/W2885569989","https://openalex.org/W3162047386","https://openalex.org/W3210390693","https://openalex.org/W3134768068","https://openalex.org/W2556931687","https://openalex.org/W4388336431","https://openalex.org/W4280555366","https://openalex.org/W2138071539"],"abstract_inverted_index":{"A":[0,55],"critical":[1],"aspect":[2],"of":[3,32,81],"modeling":[4],"binomial":[5],"response":[6],"data":[7,53,165],"is":[8,60,103],"selecting":[9],"an":[10,15,30],"appropriate":[11],"link":[12,28],"function,":[13],"as":[14],"improper":[16],"choice":[17],"can":[18],"significantly":[19],"affect":[20],"model":[21,102,157],"precision.":[22],"This":[23],"paper":[24],"introduces":[25],"the":[26,33,68,75,101,134,140,155],"skew\u2013t":[27],"model,":[29,35],"extension":[31],"skew\u2013probit":[34,135],"offering":[36],"increased":[37],"flexibility":[38],"by":[39,149],"incorporating":[40],"both":[41,121],"asymmetry":[42,69,167],"and":[43,51,89,98,114,133,145,151,168],"heavy":[44],"tails,":[45],"making":[46],"it":[47],"suitable":[48],"for":[49,67],"asymmetric":[50,152],"complex":[52,169],"structures.":[54,170],"penalized":[56],"likelihood-based":[57],"estimation":[58],"method":[59],"proposed":[61,156],"to":[62,92,105,117,127,143],"stabilize":[63],"parameter":[64],"estimation,":[65],"particularly":[66],"parameter.":[70],"Extensive":[71],"simulation":[72],"studies":[73],"demonstrate":[74],"model\u2019s":[76,141],"superior":[77,123],"performance":[78],"in":[79,161],"terms":[80],"lower":[82],"bias,":[83],"root":[84],"mean":[85],"squared":[86],"error":[87],"(RMSE),":[88],"robustness":[90],"compared":[91,126],"traditional":[93,129],"symmetric":[94],"models":[95,130],"like":[96],"probit":[97,132],"logit.":[99],"Furthermore,":[100],"applied":[104,160],"two":[106],"real-world":[107],"datasets:":[108],"one":[109],"concerning":[110],"women\u2019s":[111],"labor":[112],"participation":[113],"another":[115],"related":[116],"cardiovascular":[118],"disease":[119],"outcomes,":[120],"showing":[122],"fitting":[124],"capabilities":[125],"more":[128],"(with":[131],"links).":[136],"These":[137],"findings":[138],"highlight":[139],"applicability":[142],"socioeconomic":[144],"medical":[146],"research,":[147],"characterized":[148],"skew":[150],"data.":[153],"Moreover,":[154],"could":[158],"be":[159],"various":[162],"domains":[163],"where":[164],"exhibit":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2024-11-02T00:00:00"}