Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/31063
Authors: 
Holzmann, Hajo
Min, Aleksey
Czado, Claudia
Year of Publication: 
2006
Series/Report no.: 
Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 478
Abstract: 
A 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.
Subjects: 
asymptotic normality
linear regression
model selection
model validation
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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