@techreport{Holzmann2006Validating,
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.},
address = {M\"{u}nchen},
author = {Hajo Holzmann and Aleksey Min and Claudia Czado},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {310; asymptotic normality; linear regression; model selection; model validation},
language = {eng},
note = {urn:nbn:de:bvb:19-epub-1846-3},
number = {478},
publisher = {Techn. Univ.; Sonderforschungsbereich 386, Statistische Analyse Diskreter Strukturen},
title = {Validating linear restrictions in linear regression models with general error structure},
type = {Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universit\"{a}t M\"{u}nchen},
url = {http://hdl.handle.net/10419/31063},
year = {2006}
}
