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Description
  • Pokud je porušena podmínka ortogonality, je odhad regresních koeficientů pořízený metodou nejmenších čtverců vychýlený. Odhad je třeba provést některou jinou metodou, např. pomocí instrumentálních proměnných nebo pomocí totálních nejmenších čtverců. (cs)
  • Under heteroscedasticity of the error terms the significance of explanatory variables in a linear regression model have to be established employing the White´s estimator of covariance matrix of regression coefficients, coefficients estimated by the (Ordinary) Least Squares.
  • Under heteroscedasticity of the error terms the significance of explanatory variables in a linear regression model have to be established employing the White´s estimator of covariance matrix of regression coefficients, coefficients estimated by the (Ordinary) Least Squares. (en)
Title
  • White´s estimator of covariance matrix for instrumental weighted variables
  • White´s estimator of covariance matrix for instrumental weighted variables (en)
  • Whitův odhad kovarianční matice pro instrumentální vážené proměnné (cs)
skos:prefLabel
  • White´s estimator of covariance matrix for instrumental weighted variables
  • White´s estimator of covariance matrix for instrumental weighted variables (en)
  • Whitův odhad kovarianční matice pro instrumentální vážené proměnné (cs)
skos:notation
  • RIV/67985556:_____/08:00317608!RIV09-AV0-67985556
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  • P(GA402/06/0408), Z(AV0Z10750506)
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  • 405730
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  • RIV/67985556:_____/08:00317608
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  • robustness; heteroscedasticity; Instrumental Weighted Variables; robustified White´s estimator of covariance matrix of estimates of regression coefficients by IWV (en)
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http://linked.open...ontrolniKodProRIV
  • [6AA2EDD9778A]
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  • Porto
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  • Porto
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  • Proceedings in Computational Statistics 18th Symposium
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  • Víšek, Jan Ámos
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number of pages
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  • Springer-Verlag
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  • 978-3-7908-2083-6
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