{"id":"https://openalex.org/W3017103591","doi":"https://doi.org/10.1080/03610918.2020.1752381","title":"Detection of the symmetry of model errors for partial linear single-index models","display_name":"Detection of the symmetry of model errors for partial linear single-index models","publication_year":2020,"publication_date":"2020-04-16","ids":{"openalex":"https://openalex.org/W3017103591","doi":"https://doi.org/10.1080/03610918.2020.1752381","mag":"3017103591"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2020.1752381","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1752381","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/A5039091804","display_name":"Yujie Gai","orcid":"https://orcid.org/0000-0002-4218-5440"},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Gai","raw_affiliation_strings":["School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China","institution_ids":["https://openalex.org/I137867983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020692924","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0003-4332-5182"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["College of Mathematics and Statistics, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020692924"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.216,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53703011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"51","issue":"6","first_page":"3410","last_page":"3427"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9994000196456909,"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":0.9994000196456909,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9980999827384949,"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":0.9927999973297119,"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":0.786562442779541},{"id":"https://openalex.org/keywords/empirical-likelihood","display_name":"Empirical likelihood","score":0.7689142227172852},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7391194701194763},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5684417486190796},{"id":"https://openalex.org/keywords/test-statistic","display_name":"Test statistic","score":0.5207421779632568},{"id":"https://openalex.org/keywords/asymptotic-distribution","display_name":"Asymptotic distribution","score":0.5147207379341125},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.49036359786987305},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4760265648365021},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.46739017963409424},{"id":"https://openalex.org/keywords/efficient-estimator","display_name":"Efficient estimator","score":0.4673384130001068},{"id":"https://openalex.org/keywords/partial-correlation","display_name":"Partial correlation","score":0.4568524956703186},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.4141542613506317},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.41037362813949585},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.33320164680480957},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.32946884632110596},{"id":"https://openalex.org/keywords/minimum-variance-unbiased-estimator","display_name":"Minimum-variance unbiased estimator","score":0.21843531727790833}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.786562442779541},{"id":"https://openalex.org/C2781117939","wikidata":"https://www.wikidata.org/wiki/Q5374245","display_name":"Empirical likelihood","level":3,"score":0.7689142227172852},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7391194701194763},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5684417486190796},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.5207421779632568},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.5147207379341125},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.49036359786987305},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4760265648365021},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.46739017963409424},{"id":"https://openalex.org/C35594927","wikidata":"https://www.wikidata.org/wiki/Q2265984","display_name":"Efficient estimator","level":4,"score":0.4673384130001068},{"id":"https://openalex.org/C64708745","wikidata":"https://www.wikidata.org/wiki/Q2998010","display_name":"Partial correlation","level":3,"score":0.4568524956703186},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.4141542613506317},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.41037362813949585},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.33320164680480957},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.32946884632110596},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.21843531727790833},{"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:10.1080/03610918.2020.1752381","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1752381","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":68,"referenced_works":["https://openalex.org/W1498947193","https://openalex.org/W1513098822","https://openalex.org/W1824682467","https://openalex.org/W1967289386","https://openalex.org/W1970640939","https://openalex.org/W1978644410","https://openalex.org/W1980724431","https://openalex.org/W1983470740","https://openalex.org/W1983593003","https://openalex.org/W1984280847","https://openalex.org/W1984764931","https://openalex.org/W1989611561","https://openalex.org/W1992147656","https://openalex.org/W2001305731","https://openalex.org/W2005890854","https://openalex.org/W2008477616","https://openalex.org/W2010353172","https://openalex.org/W2010659652","https://openalex.org/W2018009091","https://openalex.org/W2019076038","https://openalex.org/W2020371156","https://openalex.org/W2022162244","https://openalex.org/W2024547771","https://openalex.org/W2032010164","https://openalex.org/W2034180713","https://openalex.org/W2034404875","https://openalex.org/W2039012334","https://openalex.org/W2045740853","https://openalex.org/W2064593219","https://openalex.org/W2075101818","https://openalex.org/W2077083909","https://openalex.org/W2081958497","https://openalex.org/W2089748799","https://openalex.org/W2090520128","https://openalex.org/W2090826008","https://openalex.org/W2093357218","https://openalex.org/W2093738981","https://openalex.org/W2101845637","https://openalex.org/W2134182851","https://openalex.org/W2136175429","https://openalex.org/W2153097785","https://openalex.org/W2198914756","https://openalex.org/W2219951363","https://openalex.org/W2275719586","https://openalex.org/W2330406605","https://openalex.org/W2376601484","https://openalex.org/W2550910743","https://openalex.org/W2560004879","https://openalex.org/W2588139202","https://openalex.org/W2610129649","https://openalex.org/W2755986143","https://openalex.org/W2782572043","https://openalex.org/W2797333853","https://openalex.org/W2910780827","https://openalex.org/W2915798644","https://openalex.org/W2918836082","https://openalex.org/W2954732189","https://openalex.org/W2969479000","https://openalex.org/W2975630066","https://openalex.org/W2989511853","https://openalex.org/W2995301308","https://openalex.org/W3037279333","https://openalex.org/W3098350919","https://openalex.org/W3099079085","https://openalex.org/W3102693992","https://openalex.org/W4210688903","https://openalex.org/W4230173782","https://openalex.org/W7056100527"],"related_works":["https://openalex.org/W2072145370","https://openalex.org/W1963855863","https://openalex.org/W2486396999","https://openalex.org/W2067937539","https://openalex.org/W2109809653","https://openalex.org/W2890145236","https://openalex.org/W2048431626","https://openalex.org/W2584466131","https://openalex.org/W2670534200","https://openalex.org/W2031443741"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,51,67],"propose":[4,52],"a":[5,53,93],"k-th":[6,29,58,73],"correlation":[7,30,59,74],"coefficient":[8,31,60,75],"estimator":[9,32,56,76],"between":[10],"the":[11,18,38,42,72,79,108,111],"density":[12,39],"function":[13,16,40],"and":[14,24,61,114],"distribution":[15,96],"of":[17,41,57,71,99,110],"model":[19,44],"errors":[20],"in":[21],"single-index":[22],"models":[23],"partial":[25],"linear":[26],"single-models.":[27],"This":[28],"is":[33,46,87],"used":[34],"to":[35,89,106],"test":[36,115],"whether":[37],"true":[43],"error":[45],"symmetric":[47],"or":[48],"not.":[49],"First,":[50],"moment":[54],"based":[55],"present":[62],"its":[63],"asymptotic":[64],"results.":[65],"Second,":[66],"consider":[68],"statistical":[69],"inference":[70],"by":[77],"using":[78],"empirical":[80,84],"likelihood":[81,85],"method.":[82],"The":[83],"statistic":[86],"shown":[88],"be":[90],"asymptotically":[91],"distributed":[92],"centered":[94],"chi-squared":[95],"with":[97],"degree":[98],"freedom":[100],"one.":[101],"Simulation":[102],"studies":[103],"are":[104],"conducted":[105],"examine":[107],"performance":[109],"proposed":[112],"estimators":[113],"statistics.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
