About: Unit-weighted regression

An Entity of Type: Thing, from Named Graph: http://dbpedia.org, within Data Space: dbpedia.org

In statistics, unit-weighted regression is a simplified and robust version (Wainer & Thissen, 1976) of multiple regression analysis where only the intercept term is estimated. That is, it fits a model where each of the are binary variables, perhaps multiplied with an arbitrary weight. Contrast this with the more common multiple regression model, where each predictor has its own estimated coefficient:

Property Value
dbo:abstract
  • In statistics, unit-weighted regression is a simplified and robust version (Wainer & Thissen, 1976) of multiple regression analysis where only the intercept term is estimated. That is, it fits a model where each of the are binary variables, perhaps multiplied with an arbitrary weight. Contrast this with the more common multiple regression model, where each predictor has its own estimated coefficient: In the social sciences, unit-weighted regression is sometimes used for binary classification, i.e. to predict a yes-no answer where indicates "no", "yes". It is easier to interpret than multiple linear regression (known as linear discriminant analysis in the classification case). (en)
dbo:wikiPageExternalLink
dbo:wikiPageID
  • 3620926 (xsd:integer)
dbo:wikiPageLength
  • 17435 (xsd:nonNegativeInteger)
dbo:wikiPageRevisionID
  • 1116600575 (xsd:integer)
dbo:wikiPageWikiLink
dbp:wikiPageUsesTemplate
dcterms:subject
rdfs:comment
  • In statistics, unit-weighted regression is a simplified and robust version (Wainer & Thissen, 1976) of multiple regression analysis where only the intercept term is estimated. That is, it fits a model where each of the are binary variables, perhaps multiplied with an arbitrary weight. Contrast this with the more common multiple regression model, where each predictor has its own estimated coefficient: (en)
rdfs:label
  • Unit-weighted regression (en)
owl:sameAs
prov:wasDerivedFrom
foaf:isPrimaryTopicOf
is dbo:knownFor of
is dbo:wikiPageWikiLink of
is dbp:knownFor of
is foaf:primaryTopic of
Powered by OpenLink Virtuoso    This material is Open Knowledge     W3C Semantic Web Technology     This material is Open Knowledge    Valid XHTML + RDFa
This content was extracted from Wikipedia and is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License