{"id":"https://openalex.org/W4323319001","doi":"https://doi.org/10.1080/03610918.2023.2186874","title":"A new ridge estimator for linear regression model with some challenging behavior of error term","display_name":"A new ridge estimator for linear regression model with some challenging behavior of error term","publication_year":2023,"publication_date":"2023-03-06","ids":{"openalex":"https://openalex.org/W4323319001","doi":"https://doi.org/10.1080/03610918.2023.2186874"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2023.2186874","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2186874","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/A5060539769","display_name":"Maha Shabbir","orcid":"https://orcid.org/0000-0002-1525-2505"},"institutions":[{"id":"https://openalex.org/I172780181","display_name":"University of the Punjab","ror":"https://ror.org/011maz450","country_code":"PK","type":"education","lineage":["https://openalex.org/I172780181"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Maha Shabbir","raw_affiliation_strings":["College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan","institution_ids":["https://openalex.org/I172780181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002838365","display_name":"Sohail Chand","orcid":"https://orcid.org/0000-0002-4564-143X"},"institutions":[{"id":"https://openalex.org/I172780181","display_name":"University of the Punjab","ror":"https://ror.org/011maz450","country_code":"PK","type":"education","lineage":["https://openalex.org/I172780181"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Sohail Chand","raw_affiliation_strings":["College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan","institution_ids":["https://openalex.org/I172780181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058065160","display_name":"Farhat Iqbal","orcid":"https://orcid.org/0000-0002-8579-0966"},"institutions":[{"id":"https://openalex.org/I20561161","display_name":"University of Balochistan","ror":"https://ror.org/04bf33n91","country_code":"PK","type":"education","lineage":["https://openalex.org/I20561161"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Farhat Iqbal","raw_affiliation_strings":["Department of Statistics, University of Balochistan, Quetta, Pakistan"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Balochistan, Quetta, Pakistan","institution_ids":["https://openalex.org/I20561161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002838365"],"corresponding_institution_ids":["https://openalex.org/I172780181"],"apc_list":null,"apc_paid":null,"fwci":6.7755,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.97693669,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"53","issue":"11","first_page":"5442","last_page":"5452"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9998000264167786,"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":0.9998000264167786,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9352999925613403,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9164999723434448,"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/multicollinearity","display_name":"Multicollinearity","score":0.8965380191802979},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7743436098098755},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.6553988456726074},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6364353895187378},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6051260828971863},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5545307397842407},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.5309908986091614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5304514765739441},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5072281360626221},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5072236061096191},{"id":"https://openalex.org/keywords/collinearity","display_name":"Collinearity","score":0.497971773147583},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.46762996912002563},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.41857343912124634},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0651395320892334}],"concepts":[{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.8965380191802979},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7743436098098755},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.6553988456726074},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6364353895187378},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6051260828971863},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5545307397842407},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.5309908986091614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5304514765739441},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5072281360626221},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5072236061096191},{"id":"https://openalex.org/C106192678","wikidata":"https://www.wikidata.org/wiki/Q1419761","display_name":"Collinearity","level":2,"score":0.497971773147583},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.46762996912002563},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.41857343912124634},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0651395320892334},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2023.2186874","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2186874","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":18,"referenced_works":["https://openalex.org/W1997227184","https://openalex.org/W1999187230","https://openalex.org/W2008320499","https://openalex.org/W2020364685","https://openalex.org/W2047263004","https://openalex.org/W2073334899","https://openalex.org/W2164888939","https://openalex.org/W2546581532","https://openalex.org/W2911659915","https://openalex.org/W2946326885","https://openalex.org/W2947134793","https://openalex.org/W3022426365","https://openalex.org/W3091007442","https://openalex.org/W3153703898","https://openalex.org/W4234698323","https://openalex.org/W4244230525","https://openalex.org/W4297826343","https://openalex.org/W6789395037"],"related_works":["https://openalex.org/W1987707056","https://openalex.org/W2963878163","https://openalex.org/W2384030147","https://openalex.org/W4234250504","https://openalex.org/W2081935514","https://openalex.org/W4231441142","https://openalex.org/W2076812056","https://openalex.org/W4386223371","https://openalex.org/W1983422301","https://openalex.org/W3015020719"],"abstract_inverted_index":{"Ridge":[0],"regression":[1,7,74,92],"is":[2,60,80,118,140],"a":[3,35,61],"variant":[4],"of":[5,14,52,63,66,72,86,112,136,146],"linear":[6,91],"that":[8,120],"aims":[9],"to":[10,38,43,82],"circumvent":[11],"the":[12,27,40,46,53,64,69,73,84,87,90,110,121,134,137,143],"issue":[13],"collinearity":[15],"among":[16],"predictors.":[17],"The":[18,56],"ridge":[19,41,58],"parameter":[20,42],"k":[21],"has":[22],"an":[23],"important":[24],"role":[25],"in":[26],"bias-variance":[28],"tradeoff.":[29],"In":[30],"this":[31],"article,":[32],"we":[33],"introduce":[34],"new":[36,122],"approach":[37],"select":[39],"deal":[44],"with":[45,49,94],"multicollinearity":[47],"problem":[48],"different":[50,95],"behavior":[51],"error":[54,71,96,115],"term.":[55],"proposed":[57,123,138],"estimator":[59,124,139],"function":[62],"number":[65],"predictors":[67],"and":[68,103,129],"standard":[70],"model.":[75],"An":[76],"extensive":[77],"simulation":[78],"study":[79],"conducted":[81],"assess":[83],"performance":[85],"estimators":[88],"for":[89],"model":[93],"terms,":[97],"which":[98],"include":[99],"normally":[100],"distributed,":[101],"non-normal":[102],"heteroscedastic":[104],"or":[105],"autocorrelated":[106],"errors.":[107],"Based":[108],"upon":[109],"criterion":[111],"mean":[113],"square":[114],"(MSE),":[116],"it":[117],"found":[119],"outperforms":[125],"OLS,":[126],"commonly":[127],"used":[128],"closely":[130],"related":[131],"estimators.":[132],"Further,":[133],"application":[135],"provided":[141],"on":[142],"COVID-19":[144],"data":[145],"India.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}