{"id":"https://openalex.org/W2286581362","doi":"https://doi.org/10.1080/03610918.2015.1091078","title":"Performance of Wald-type estimator for parametric component in partial linear regression with a mixture of Berkson and classical error models","display_name":"Performance of Wald-type estimator for parametric component in partial linear regression with a mixture of Berkson and classical error models","publication_year":2015,"publication_date":"2015-10-15","ids":{"openalex":"https://openalex.org/W2286581362","doi":"https://doi.org/10.1080/03610918.2015.1091078","mag":"2286581362"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2015.1091078","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1091078","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/A5020142071","display_name":"Yuh\u2010Jenn Wu","orcid":"https://orcid.org/0009-0004-3298-3942"},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yuh-Jenn Wu","raw_affiliation_strings":["Department of Applied Mathematics, Chung Yuan Christian University, Chung Li, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Chung Yuan Christian University, Chung Li, Taiwan, R.O.C","institution_ids":["https://openalex.org/I151221077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054185259","display_name":"Wei-Quan Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Wei-Quan Fang","raw_affiliation_strings":["Department of Applied Mathematics, Chung Yuan Christian University, Chung Li, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Chung Yuan Christian University, Chung Li, Taiwan, R.O.C","institution_ids":["https://openalex.org/I151221077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054185259"],"corresponding_institution_ids":["https://openalex.org/I151221077"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13206379,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9997000098228455,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9997000098228455,"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":0.9941999912261963,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6938039064407349},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6413216590881348},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5736226439476013},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5580344200134277},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5374010801315308},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.49796557426452637},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.48606470227241516},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.45881232619285583},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.43337997794151306}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6938039064407349},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6413216590881348},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5736226439476013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5580344200134277},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5374010801315308},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.49796557426452637},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.48606470227241516},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.45881232619285583},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43337997794151306},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2015.1091078","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1091078","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W135795571","https://openalex.org/W611112179","https://openalex.org/W995194104","https://openalex.org/W1541572574","https://openalex.org/W1621793539","https://openalex.org/W1824682467","https://openalex.org/W1971077067","https://openalex.org/W1982171259","https://openalex.org/W1982475765","https://openalex.org/W1995026811","https://openalex.org/W1999607897","https://openalex.org/W2009314534","https://openalex.org/W2011627547","https://openalex.org/W2013915870","https://openalex.org/W2014743371","https://openalex.org/W2022796289","https://openalex.org/W2026810457","https://openalex.org/W2031008088","https://openalex.org/W2040785119","https://openalex.org/W2042089645","https://openalex.org/W2046993457","https://openalex.org/W2056481711","https://openalex.org/W2063494739","https://openalex.org/W2065725171","https://openalex.org/W2068665745","https://openalex.org/W2080040321","https://openalex.org/W2083123688","https://openalex.org/W2085166207","https://openalex.org/W2090382595","https://openalex.org/W2121404925","https://openalex.org/W2129676238","https://openalex.org/W2129697223","https://openalex.org/W2155044034","https://openalex.org/W2321428642","https://openalex.org/W2337577258","https://openalex.org/W2797841545","https://openalex.org/W3000332379","https://openalex.org/W3042168128","https://openalex.org/W3099204701","https://openalex.org/W3102146195","https://openalex.org/W3143949042","https://openalex.org/W4213097923","https://openalex.org/W4237374278","https://openalex.org/W4248402653"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4385769873","https://openalex.org/W2015759683","https://openalex.org/W4281634296","https://openalex.org/W4319161863","https://openalex.org/W2357256365","https://openalex.org/W2371687270","https://openalex.org/W4307819175"],"abstract_inverted_index":{"This":[0],"article":[1],"discusses":[2],"a":[3,24,77],"consistent":[4],"and":[5,28,40,59],"almost":[6],"unbiased":[7],"estimation":[8,63],"approach":[9,88],"in":[10,76,92],"partial":[11],"linear":[12],"regression":[13],"for":[14],"parameters":[15],"of":[16,26,32,64,72,79,95],"interest":[17],"when":[18],"the":[19,33,62,70,93],"regressors":[20],"are":[21,42],"contaminated":[22],"with":[23],"mixture":[25],"Berkson":[27],"classical":[29],"errors.":[30],"Advantages":[31],"presented":[34,74],"procedure":[35],"are:":[36],"(1)":[37],"random":[38],"errors":[39],"observations":[41],"not":[43],"necessarily":[44],"to":[45,54,60],"be":[46],"parametric":[47],"settings;":[48],"(2)":[49],"there":[50],"is":[51,89],"no":[52],"need":[53],"use":[55],"additional":[56],"sample":[57],"information,":[58],"consider":[61],"nuisance":[65],"parameters.":[66],"We":[67],"will":[68],"examine":[69],"performance":[71],"our":[73],"estimate":[75],"variety":[78],"numerical":[80],"examples":[81],"through":[82],"Monte":[83],"Carlo":[84],"simulation.":[85],"The":[86],"proposed":[87],"also":[90],"illustrated":[91],"analysis":[94],"an":[96],"air":[97],"pollution":[98],"data.":[99]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
