Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/19606
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dc.creatorSamorodnitsky, Gennady-
dc.creatorRachev, Svetlozar T.-
dc.creatorKurz-Kim, Jeong-Ryeol-
dc.date2005-
dc.date.accessioned2013-10-16T07:05:53Z-
dc.date.available2013-10-16T07:05:53Z-
dc.date.issued2013-10-16-
dc.identifierhttp://hdl.handle.net/10419/19606-
dc.identifierppn:49586241X-
dc.identifierRePEc:zbw:bubdp1:4215-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/10419/19606-
dc.descriptionUnder the symmetric á-stable distributional assumption for the disturbances, Blattberg et al (1971) consider unbiased linear estimators for a regression model with non-stochastic regressors. We consider both the rate of convergence to the true value and the asymptotic distribution of the normalized error of the linear unbiased estimators. By doing this, we allow the regressors to be stochastic and disturbances to be heavy-tailed with either finite or infinite variances, where the tail-thickness parameters of the regressors and disturbances may be different.-
dc.languageeng-
dc.relationDiscussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2005,21-
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.subjectddc:330-
dc.subjectAsymptotic distribution-
dc.subjectrate of convergence-
dc.subjectstochastic regressor-
dc.subjectstable non-Gaussian-
dc.subjectfinite or infinite variance-
dc.subjectheavy tails-
dc.subjectRegression-
dc.subjectSchätztheorie-
dc.subjectStatistische Verteilung-
dc.subjectTheorie-
dc.titleAsymptotic distribution of linear unbiased estimators in the presence of heavy-tailed stochastic regressors and residuals-
dc.typedoc-type:workingPaper-
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