{"id":"https://openalex.org/W4382138662","doi":"https://doi.org/10.1080/03610918.2023.2224945","title":"Quantile regression based on the skewed exponential power distribution","display_name":"Quantile regression based on the skewed exponential power distribution","publication_year":2023,"publication_date":"2023-06-25","ids":{"openalex":"https://openalex.org/W4382138662","doi":"https://doi.org/10.1080/03610918.2023.2224945"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2023.2224945","is_oa":true,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2224945","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/03610918.2023.2224945?needAccess=true&role=button","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":true,"oa_status":"hybrid","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/03610918.2023.2224945?needAccess=true&role=button","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053479979","display_name":"Lukas Arnroth","orcid":"https://orcid.org/0000-0002-8567-5116"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Lukas Arnroth","raw_affiliation_strings":["Department of Statistics, Uppsala University, Uppsala, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045102517","display_name":"Johan Vegelius","orcid":"https://orcid.org/0000-0002-0497-0659"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Johan Vegelius","raw_affiliation_strings":["Department of Statistics, Uppsala University, Uppsala, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053479979"],"corresponding_institution_ids":["https://openalex.org/I123387679"],"apc_list":null,"apc_paid":null,"fwci":3.159,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92668637,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"53","issue":"12","first_page":"6189","last_page":"6205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9975000023841858,"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":0.9975000023841858,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.996999979019165,"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":0.9965999722480774,"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/quantile-regression","display_name":"Quantile regression","score":0.7792831659317017},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.6919073462486267},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.6695321798324585},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6353532075881958},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6068830490112305},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5590587258338928},{"id":"https://openalex.org/keywords/laplace-distribution","display_name":"Laplace distribution","score":0.4985041618347168},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.46600112318992615},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.45784467458724976},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.410757452249527},{"id":"https://openalex.org/keywords/exponential-distribution","display_name":"Exponential distribution","score":0.38368213176727295},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.24002349376678467}],"concepts":[{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.7792831659317017},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.6919073462486267},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.6695321798324585},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6353532075881958},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6068830490112305},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5590587258338928},{"id":"https://openalex.org/C183057437","wikidata":"https://www.wikidata.org/wiki/Q671617","display_name":"Laplace distribution","level":3,"score":0.4985041618347168},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.46600112318992615},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.45784467458724976},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.410757452249527},{"id":"https://openalex.org/C55350006","wikidata":"https://www.wikidata.org/wiki/Q237193","display_name":"Exponential distribution","level":2,"score":0.38368213176727295},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.24002349376678467}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/03610918.2023.2224945","is_oa":true,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2224945","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/03610918.2023.2224945?needAccess=true&role=button","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},{"id":"pmh:oai:DiVA.org:uu-507344","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-507344","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1080/03610918.2023.2224945","is_oa":true,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2224945","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/03610918.2023.2224945?needAccess=true&role=button","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4382138662.pdf","grobid_xml":"https://content.openalex.org/works/W4382138662.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1545319692","https://openalex.org/W2001203190","https://openalex.org/W2031188467","https://openalex.org/W2033765726","https://openalex.org/W2044551864","https://openalex.org/W2084871407","https://openalex.org/W2094407065","https://openalex.org/W2120575449","https://openalex.org/W2152873044","https://openalex.org/W2562019904","https://openalex.org/W2581839231","https://openalex.org/W2760574762","https://openalex.org/W2790844269","https://openalex.org/W2801092597","https://openalex.org/W2884758310","https://openalex.org/W2963032105","https://openalex.org/W4241653265"],"related_works":["https://openalex.org/W4206511378","https://openalex.org/W4206618949","https://openalex.org/W2526321210","https://openalex.org/W3205863630","https://openalex.org/W3014605311","https://openalex.org/W2364275385","https://openalex.org/W4388704167","https://openalex.org/W4318833145","https://openalex.org/W2007977664","https://openalex.org/W4376874882"],"abstract_inverted_index":{"Bayesian":[0,30],"quantile":[1,60,66],"regression":[2,20],"generally":[3,74],"relies":[4],"on":[5,22,43],"the":[6,12,23,44,88,92],"asymmetric":[7],"Laplace":[8],"distribution":[9,27],"(ALD)":[10],"as":[11],"error":[13,83],"distribution.":[14],"We":[15,46],"consider":[16],"methods":[17,51,73],"for":[18],"Lp-quantile":[19],"based":[21,42],"skewed":[24],"exponential":[25],"power":[26],"(SEPD).":[28],"Both":[29],"and":[31,37],"frequentist":[32],"estimation":[33],"procedures":[34],"are":[35],"outlined":[36],"compared":[38,63],"with":[39,64],"previous":[40,55],"work":[41],"SEPD.":[45],"find":[47,69],"that":[48,70],"our":[49,71],"proposed":[50,72,93],"greatly":[52],"outperform":[53],"a":[54,98,102],"method":[56],"in":[57,77],"terms":[58,78],"of":[59,79,87,91],"estimation.":[61],"Further,":[62,101],"standard":[65],"regression,":[67],"we":[68],"perform":[75],"better":[76],"root":[80],"mean":[81],"square":[82],"(RMSE).":[84],"Empirical":[85],"evidence":[86],"statistical":[89],"properties":[90],"models":[94],"is":[95],"provided":[96],"through":[97],"simulation":[99],"study.":[100],"real":[103],"data":[104],"application":[105],"illustrates":[106],"their":[107],"performance.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
