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- W4387233114 abstract "In this paper we present estimated generalized least squares (EGLS) estimator for the coefficient vector β in the linear regression model y = βX + ε, where disturbance term can be heteroskedastic. For the heteroskedasticity of the changed segment type, using Monte-Carlo method, we investigate empirical properties of the proposed and ordinary least squares (OLS) estimators. The results show that the empirical covariance of the EGLS estimators is smaller than that of OLS estimators." @default.
- W4387233114 created "2023-10-02" @default.
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- W4387233114 date "2023-09-21" @default.
- W4387233114 modified "2023-10-16" @default.
- W4387233114 title "Properties of the coefficient estimators for the linear regression model with heteroskedastic error term" @default.
- W4387233114 doi "https://doi.org/10.15388/lmr.2006.30725" @default.
- W4387233114 hasPublicationYear "2023" @default.
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