{"id":"https://openalex.org/W4200195502","doi":"https://doi.org/10.1080/03610918.2021.2020289","title":"A family of asymmetric kernels based on log-symmetric distributions","display_name":"A family of asymmetric kernels based on log-symmetric distributions","publication_year":2021,"publication_date":"2021-12-28","ids":{"openalex":"https://openalex.org/W4200195502","doi":"https://doi.org/10.1080/03610918.2021.2020289"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2021.2020289","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.2020289","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/A5026737230","display_name":"Sylia Makhloufi","orcid":null},"institutions":[{"id":"https://openalex.org/I187560010","display_name":"University of B\u00e9ja\u00efa","ror":"https://ror.org/03yb2hp88","country_code":"DZ","type":"education","lineage":["https://openalex.org/I187560010"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"S. Makhloufi","raw_affiliation_strings":["Operational Research Department, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria","Research Unit LaMOS, University of Bejaia, Bejaia, Algeria"],"affiliations":[{"raw_affiliation_string":"Operational Research Department, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria","institution_ids":["https://openalex.org/I187560010"]},{"raw_affiliation_string":"Research Unit LaMOS, University of Bejaia, Bejaia, Algeria","institution_ids":["https://openalex.org/I187560010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090280933","display_name":"Nabil Zougab","orcid":null},"institutions":[{"id":"https://openalex.org/I187560010","display_name":"University of B\u00e9ja\u00efa","ror":"https://ror.org/03yb2hp88","country_code":"DZ","type":"education","lineage":["https://openalex.org/I187560010"]}],"countries":["DZ"],"is_corresponding":true,"raw_author_name":"N. Zougab","raw_affiliation_strings":["Department of Electrical Engineering, Faculty of Technology, University of Bejaia, Bejaia, Algeria","Research Unit LaMOS, University of Bejaia, Bejaia, Algeria"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Technology, University of Bejaia, Bejaia, Algeria","institution_ids":["https://openalex.org/I187560010"]},{"raw_affiliation_string":"Research Unit LaMOS, University of Bejaia, Bejaia, Algeria","institution_ids":["https://openalex.org/I187560010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053245137","display_name":"Ydriss Ziane","orcid":"https://orcid.org/0000-0003-2104-3459"},"institutions":[{"id":"https://openalex.org/I187560010","display_name":"University of B\u00e9ja\u00efa","ror":"https://ror.org/03yb2hp88","country_code":"DZ","type":"education","lineage":["https://openalex.org/I187560010"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Y. Ziane","raw_affiliation_strings":["Research Unit LaMOS, University of Bejaia, Bejaia, Algeria"],"affiliations":[{"raw_affiliation_string":"Research Unit LaMOS, University of Bejaia, Bejaia, Algeria","institution_ids":["https://openalex.org/I187560010"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053585589","display_name":"Sma\u00efl Adjabi","orcid":"https://orcid.org/0000-0001-5024-6322"},"institutions":[{"id":"https://openalex.org/I187560010","display_name":"University of B\u00e9ja\u00efa","ror":"https://ror.org/03yb2hp88","country_code":"DZ","type":"education","lineage":["https://openalex.org/I187560010"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"S. Adjabi","raw_affiliation_strings":["Research Unit LaMOS, University of Bejaia, Bejaia, Algeria"],"affiliations":[{"raw_affiliation_string":"Research Unit LaMOS, University of Bejaia, Bejaia, Algeria","institution_ids":["https://openalex.org/I187560010"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090280933"],"corresponding_institution_ids":["https://openalex.org/I187560010"],"apc_list":null,"apc_paid":null,"fwci":0.464,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68824464,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"53","issue":"1","first_page":"380","last_page":"397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9988999962806702,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9988999962806702,"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":0.9919999837875366,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9818000197410583,"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/estimator","display_name":"Estimator","score":0.7501638531684875},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7439212203025818},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.6717231869697571},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5401159524917603},{"id":"https://openalex.org/keywords/multivariate-kernel-density-estimation","display_name":"Multivariate kernel density estimation","score":0.5086246728897095},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.5001070499420166},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.481020987033844},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.47808361053466797},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.45411255955696106},{"id":"https://openalex.org/keywords/inverse-gaussian-distribution","display_name":"Inverse Gaussian distribution","score":0.4492250978946686},{"id":"https://openalex.org/keywords/delta-method","display_name":"Delta method","score":0.44305840134620667},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4360448122024536},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.41534990072250366},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38875535130500793},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.37383073568344116},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.21231016516685486},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2064596712589264},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.14188158512115479},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12636908888816833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12329119443893433}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7501638531684875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7439212203025818},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.6717231869697571},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5401159524917603},{"id":"https://openalex.org/C84894716","wikidata":"https://www.wikidata.org/wiki/Q6935135","display_name":"Multivariate kernel density estimation","level":5,"score":0.5086246728897095},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5001070499420166},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.481020987033844},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.47808361053466797},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.45411255955696106},{"id":"https://openalex.org/C132878287","wikidata":"https://www.wikidata.org/wiki/Q1671727","display_name":"Inverse Gaussian distribution","level":3,"score":0.4492250978946686},{"id":"https://openalex.org/C971699","wikidata":"https://www.wikidata.org/wiki/Q1132714","display_name":"Delta method","level":3,"score":0.44305840134620667},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4360448122024536},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.41534990072250366},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38875535130500793},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.37383073568344116},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.21231016516685486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2064596712589264},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.14188158512115479},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12636908888816833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12329119443893433},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2021.2020289","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.2020289","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W178256187","https://openalex.org/W1138027541","https://openalex.org/W1492095942","https://openalex.org/W1879048345","https://openalex.org/W1975962966","https://openalex.org/W1978135292","https://openalex.org/W1984854447","https://openalex.org/W1994083140","https://openalex.org/W1994376651","https://openalex.org/W2009705985","https://openalex.org/W2019555413","https://openalex.org/W2029698240","https://openalex.org/W2039205468","https://openalex.org/W2041197027","https://openalex.org/W2041365877","https://openalex.org/W2044564187","https://openalex.org/W2055017467","https://openalex.org/W2055599454","https://openalex.org/W2058000970","https://openalex.org/W2088242343","https://openalex.org/W2089436810","https://openalex.org/W2091955409","https://openalex.org/W2094964791","https://openalex.org/W2144034880","https://openalex.org/W2167758633","https://openalex.org/W2171916513","https://openalex.org/W2325468794","https://openalex.org/W2340317884","https://openalex.org/W2466712920","https://openalex.org/W2481824080","https://openalex.org/W2514056720","https://openalex.org/W2514831868","https://openalex.org/W2534499044","https://openalex.org/W2752367740","https://openalex.org/W2757814065","https://openalex.org/W2770651489","https://openalex.org/W2792810684","https://openalex.org/W2796475746","https://openalex.org/W2807358544","https://openalex.org/W2901673343","https://openalex.org/W2918113287","https://openalex.org/W2955205486","https://openalex.org/W3101386208","https://openalex.org/W4233014035"],"related_works":["https://openalex.org/W4241010850","https://openalex.org/W3212687977","https://openalex.org/W4251965284","https://openalex.org/W2583877436","https://openalex.org/W1834385407","https://openalex.org/W2355371556","https://openalex.org/W4239457139","https://openalex.org/W4386285810","https://openalex.org/W3123419490","https://openalex.org/W2144201579"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3],"class":[4],"of":[5,21,36,46,63,98],"asymmetric":[6],"kernels":[7,93],"based":[8],"on":[9,108],"log-symmetric":[10],"(LS)":[11],"distributions":[12],"for":[13,83],"probability":[14],"density":[15,40,68,81],"function":[16],"estimation":[17,82],"in":[18],"the":[19,37,52,61,64,75],"context":[20],"strictly":[22],"positive":[23],"skewed":[24],"data.":[25],"Some":[26],"asymptotic":[27],"properties":[28],"(bias,":[29],"variance":[30],"and":[31,54,70,89,101],"mean":[32],"integrated":[33],"squared":[34],"error)":[35],"LS":[38,66,77],"kernel":[39,67,78],"estimators":[41,69,79],"are":[42],"established.":[43],"The":[44],"choice":[45],"bandwidth":[47],"is":[48,111],"investigated":[49],"by":[50],"adapting":[51],"rule-of-thumb":[53],"cross-validation":[55],"methods.":[56],"A":[57],"simulation":[58],"study":[59],"investigates":[60],"performance":[62],"proposed":[65],"compare":[71],"their":[72],"performances":[73],"with":[74],"Kakizawa\u2019s":[76],"[Nonparametric":[80],"nonnegative":[84],"data,":[85],"using":[86],"symmetrical-based":[87],"inverse":[88,91],"reciprocal":[90],"Gaussian":[92],"through":[94],"dual":[95],"transformation.":[96],"Journal":[97],"Statistical":[99],"Planning":[100],"Inference.":[102],"2018;":[103],"193:117\u2013135].":[104],"Finally,":[105],"an":[106],"application":[107],"real":[109],"data":[110],"analyzed.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}