{"id":"https://openalex.org/W7153851401","doi":"https://doi.org/10.1007/s00180-026-01741-7","title":"A novel unit exponential regression model with improved estimation method under multicollinearity","display_name":"A novel unit exponential regression model with improved estimation method under multicollinearity","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7153851401","doi":"https://doi.org/10.1007/s00180-026-01741-7"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-026-01741-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-026-01741-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01741-7.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01741-7.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091358729","display_name":"Alaa R. El-Alosey","orcid":"https://orcid.org/0000-0002-3177-2420"},"institutions":[{"id":"https://openalex.org/I21376657","display_name":"Tanta University","ror":"https://ror.org/016jp5b92","country_code":"EG","type":"education","lineage":["https://openalex.org/I21376657"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Alaa R. El-Alosey","raw_affiliation_strings":["Department of Mathematics, Faculty of Science, Tanta University, Tanta, 31527, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-3177-2420","affiliations":[{"raw_affiliation_string":"Department of Mathematics, Faculty of Science, Tanta University, Tanta, 31527, Egypt","institution_ids":["https://openalex.org/I21376657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129959999","display_name":"Ali T. Hammad","orcid":null},"institutions":[{"id":"https://openalex.org/I21376657","display_name":"Tanta University","ror":"https://ror.org/016jp5b92","country_code":"EG","type":"education","lineage":["https://openalex.org/I21376657"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ali T. Hammad","raw_affiliation_strings":["Department of Mathematics, Faculty of Science, Tanta University, Tanta, 31527, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Faculty of Science, Tanta University, Tanta, 31527, Egypt","institution_ids":["https://openalex.org/I21376657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5133453548","display_name":"Ahmed M. Gemeay","orcid":null},"institutions":[{"id":"https://openalex.org/I21376657","display_name":"Tanta University","ror":"https://ror.org/016jp5b92","country_code":"EG","type":"education","lineage":["https://openalex.org/I21376657"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ahmed M. Gemeay","raw_affiliation_strings":["Department of Mathematics, Faculty of Science, Tanta University, Tanta, 31527, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Faculty of Science, Tanta University, Tanta, 31527, Egypt","institution_ids":["https://openalex.org/I21376657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5091358729"],"corresponding_institution_ids":["https://openalex.org/I21376657"],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":{"value":2490,"currency":"EUR","value_usd":3090},"fwci":18.9399,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.98897114,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"41","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.7989000082015991,"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":0.7989000082015991,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.10409999638795853,"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/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.01979999989271164,"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":0.9316999912261963},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5069000124931335},{"id":"https://openalex.org/keywords/variance-inflation-factor","display_name":"Variance inflation factor","score":0.4893999993801117},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.45969998836517334},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4417000114917755},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.39169999957084656},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.38909998536109924},{"id":"https://openalex.org/keywords/principal-component-regression","display_name":"Principal component regression","score":0.3382999897003174}],"concepts":[{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.9316999912261963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6482999920845032},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5806000232696533},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C152732102","wikidata":"https://www.wikidata.org/wiki/Q13434396","display_name":"Variance inflation factor","level":4,"score":0.4893999993801117},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.39489999413490295},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.35339999198913574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3386000096797943},{"id":"https://openalex.org/C74887250","wikidata":"https://www.wikidata.org/wiki/Q3455892","display_name":"Principal component regression","level":3,"score":0.3382999897003174},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C122637931","wikidata":"https://www.wikidata.org/wiki/Q118084","display_name":"Unit (ring theory)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C93698799","wikidata":"https://www.wikidata.org/wiki/Q5428730","display_name":"Factor regression model","level":5,"score":0.30250000953674316},{"id":"https://openalex.org/C17418463","wikidata":"https://www.wikidata.org/wiki/Q3455874","display_name":"Isotonic regression","level":3,"score":0.3019999861717224},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.2955999970436096},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C185265303","wikidata":"https://www.wikidata.org/wiki/Q7309537","display_name":"Regression dilution","level":4,"score":0.27730000019073486},{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.262800008058548}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s00180-026-01741-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-026-01741-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01741-7.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s00180-026-01741-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-026-01741-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-026-01741-7.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324798","display_name":"Tanta University","ror":"https://ror.org/016jp5b92"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7153851401.pdf","grobid_xml":"https://content.openalex.org/works/W7153851401.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W121938757","https://openalex.org/W1987081668","https://openalex.org/W2018275040","https://openalex.org/W2050452596","https://openalex.org/W2111220553","https://openalex.org/W2159483927","https://openalex.org/W2240798254","https://openalex.org/W2280184700","https://openalex.org/W2314246804","https://openalex.org/W2809960452","https://openalex.org/W2900560033","https://openalex.org/W2901610751","https://openalex.org/W2903607238","https://openalex.org/W2963014117","https://openalex.org/W2971089215","https://openalex.org/W3124991750","https://openalex.org/W3187060124","https://openalex.org/W3208303142","https://openalex.org/W3214552377","https://openalex.org/W4213370044","https://openalex.org/W4226186974","https://openalex.org/W4229058015","https://openalex.org/W4241653265","https://openalex.org/W4282967003","https://openalex.org/W4295835860","https://openalex.org/W4301861531","https://openalex.org/W4377041089","https://openalex.org/W4387459835","https://openalex.org/W4389626397","https://openalex.org/W4390413824","https://openalex.org/W4404768248","https://openalex.org/W4405249535","https://openalex.org/W4412360803","https://openalex.org/W4412697687","https://openalex.org/W4412750057","https://openalex.org/W4412912639","https://openalex.org/W4412926276","https://openalex.org/W4412965996","https://openalex.org/W4413946063","https://openalex.org/W4414305517","https://openalex.org/W7083164761"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"In":[1],"regression":[2,36,54,60,98],"analysis":[3],"of":[4,81,162,183,204],"bounded":[5],"response":[6],"variables":[7,110],"on":[8,198],"the":[9,57,79,95,108,117,142,151,163,167,181,184,202,212,215,220,224,232,246],"interval":[10],"(0,1),":[11],"selecting":[12],"an":[13],"appropriate":[14,43],"model":[15,61,75,186,222],"is":[16,76,90,101,236,243],"crucial":[17],"for":[18,44,69,141,239],"accurately":[19],"identifying":[20],"relationships":[21],"with":[22],"explanatory":[23,109,247],"variables.":[24,248],"Quantile":[25],"modeling":[26,70],"widely":[27],"utilizes":[28],"established":[29],"models":[30],"like":[31],"beta":[32],"and":[33,67,125,149,166,187,206,214,231],"unit":[34,58,71],"Lindley":[35],"models,":[37,99,230],"but":[38],"they":[39],"may":[40],"not":[41],"be":[42],"most":[45],"datasets.":[46],"Therefore,":[47],"this":[48,133],"paper":[49],"introduces":[50],"a":[51,126,137],"new":[52],"quantile":[53],"model,":[55],"called":[56],"exponential":[59,83],"(UERM),":[62],"which":[63,100,144],"offers":[64],"greater":[65],"flexibility":[66],"suitability":[68,182],"data.":[72],"The":[73,85,159,208],"proposed":[74,164,185],"derived":[77],"from":[78,201,210],"family":[80],"two-parameter":[82],"distributions.":[84],"maximum":[86],"likelihood":[87],"estimation":[88],"(MLE)":[89],"usually":[91],"used":[92,178],"to":[93,146,179],"estimate":[94],"parameters":[96,240],"in":[97,120],"effective":[102],"under":[103],"standard":[104],"conditions.":[105],"However,":[106],"when":[107,241],"are":[111],"highly":[112],"correlated,":[113],"it":[114],"can":[115],"impact":[116],"MLE,":[118],"resulting":[119],"unreliable":[121],"parameters,":[122],"inflated":[123],"variance,":[124],"higher":[127],"mean":[128],"squared":[129],"error.":[130],"To":[131,189],"solve":[132],"issue,":[134],"we":[135],"suggest":[136],"better":[138,227],"Liu":[139,168,233],"estimator":[140],"UERM,":[143],"aims":[145],"reduce":[147],"multicollinearity":[148,244],"make":[150],"estimates":[152],"more":[153,237],"accurate":[154],"by":[155],"lowering":[156],"variance":[157],"inflation.":[158],"statistical":[160],"characteristics":[161],"UERM":[165,221],"estimating":[169,234],"method":[170,235],"were":[171,177,196],"examined.":[172],"Extensive":[173],"Monte":[174],"Carlo":[175],"simulations":[176,213],"assess":[180],"estimator.":[188],"demonstrate":[190],"their":[191],"scientific":[192],"validity,":[193],"experimental":[194],"applications":[195],"conducted":[197],"real-world":[199,216],"datasets":[200],"fields":[203],"health":[205],"engineering.":[207],"results":[209],"both":[211],"tests":[217],"show":[218],"that":[219],"fits":[223],"limited":[225],"data":[226],"than":[228],"existing":[229],"reliable":[238],"there":[242],"among":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2026-04-13T00:00:00"}
