EconStor >
Ludwig-Maximilians-Universität München (LMU) >
Sonderforschungsbereich 386: Statistische Analyse diskreter Strukturen, Universität München (LMU) >
Discussion papers, SFB 386, LMU München >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/31063
  

Full metadata record

DC FieldValueLanguage
dc.contributor.authorHolzmann, Hajoen_US
dc.contributor.authorMin, Alekseyen_US
dc.contributor.authorCzado, Claudiaen_US
dc.date.accessioned2006-09-07en_US
dc.date.accessioned2010-05-14T10:10:02Z-
dc.date.available2010-05-14T10:10:02Z-
dc.date.issued2006en_US
dc.identifier.piurn:nbn:de:bvb:19-epub-1846-3-
dc.identifier.urihttp://hdl.handle.net/10419/31063-
dc.description.abstractA new method for testing linear restrictions in linear regression models is suggested. It allows to validate the linear restriction, up to a specified approximation error and with a specified error probability. The test relies on asymptotic normality of the test statistic, and therefore normality of the errors in the regression model is not required. In a simulation study the performance of the suggested method for model selection purposes, as compared to standard model selection criteria and the t-test, is examined. As an illustration we analyze the US college spending data from 1994.en_US
dc.language.isoengen_US
dc.publisherTechn. Univ.; Sonderforschungsbereich 386, Statistische Analyse Diskreter Strukturen Münchenen_US
dc.relation.ispartofseriesDiscussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 478en_US
dc.subject.ddc310en_US
dc.subject.keywordasymptotic normalityen_US
dc.subject.keywordlinear regressionen_US
dc.subject.keywordmodel selectionen_US
dc.subject.keywordmodel validationen_US
dc.titleValidating linear restrictions in linear regression models with general error structureen_US
dc.typeWorking Paperen_US
dc.identifier.ppn51717104Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
Appears in Collections:Discussion papers, SFB 386, LMU München

Files in This Item:
File Description SizeFormat
51717104X.PDF309.12 kBAdobe PDF
No. of Downloads: Counter Stats
Show simple item record
Download bibliographical data as: BibTeX

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.