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Asymptotic distribution of linear unbiased estimators in the presence of heavy-tailed stochastic regressors and residuals

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dc.creator Samorodnitsky, Gennady
dc.creator Rachev, Svetlozar T.
dc.creator Kurz-Kim, Jeong-Ryeol
dc.date 2005
dc.date.accessioned 2013-10-16T07:05:53Z
dc.date.available 2013-10-16T07:05:53Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/19606
dc.identifier ppn:49586241X
dc.identifier RePEc:zbw:bubdp1:4215
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/19606
dc.description Under 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.language eng
dc.relation Discussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank 2005,21
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject ddc:330
dc.subject Asymptotic distribution
dc.subject rate of convergence
dc.subject stochastic regressor
dc.subject stable non-Gaussian
dc.subject finite or infinite variance
dc.subject heavy tails
dc.subject Regression
dc.subject Schätztheorie
dc.subject Statistische Verteilung
dc.subject Theorie
dc.title Asymptotic distribution of linear unbiased estimators in the presence of heavy-tailed stochastic regressors and residuals
dc.type doc-type:workingPaper


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