https://openalex.org/T11871
This cluster of papers focuses on the detection, impact, and handling of multicollinearity in regression analysis. It discusses methods for identifying outliers, robust estimation techniques, variance inflation factors, and the use of depth functions in analyzing data. The cluster also explores the relative importance of predictors, principal component analysis, and the application of these concepts to functional data.
@prefix oasubfields: <https://openalex.org/subfields/> .
@prefix openalex: <https://lambdamusic.github.io/openalex-hacks/ontology/> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
<https://openalex.org/T11871> a skos:Concept ;
rdfs:label "Detection and Handling of Multicollinearity in Regression Analysis"@en ;
rdfs:isDefinedBy openalex: ;
owl:sameAs <https://en.wikipedia.org/wiki/Multicollinearity>,
<https://openalex.org/T11871> ;
skos:broader oasubfields:2613 ;
skos:definition "This cluster of papers focuses on the detection, impact, and handling of multicollinearity in regression analysis. It discusses methods for identifying outliers, robust estimation techniques, variance inflation factors, and the use of depth functions in analyzing data. The cluster also explores the relative importance of predictors, principal component analysis, and the application of these concepts to functional data."@en ;
skos:inScheme openalex: ;
skos:prefLabel "Detection and Handling of Multicollinearity in Regression Analysis"@en ;
openalex:cited_by_count 2820064 ;
openalex:works_count 75441 .