Název:
On Heteroscedasticity in Robust Regression
Autoři:
Kalina, Jan Typ dokumentu: Příspěvky z konference Konference/Akce: International Days of Statistics and Economics /5./, Prague (CZ), 2011-09-22 / 2011-09-23
Rok:
2011
Jazyk:
eng
Abstrakt: This work studies the phenomenon of heteroscedasticity and its consequences for various methods of linear regression, including the least squares, least weighted squares and regression quantiles. We focus on hypothesis tests for these regression methods. The new approach consists in deriving asymptotic heteroscedasticity tests for robust regression, which are asymptotically equivalent to standard tests computed for the least squares regression. One approach to modeling heteroscedasticity assumes a prior knowledge or specific model for the variability of random regression errors. Another (and more general) approach does not assume a specific form of heteroscedasticity. The paper also describes heteroscedastic regression, which is a tool to incorporate heteroscedasticity to the model. This allows us to define the heteroscedastic least weighted squares regression.
Klíčová slova:
diagnostics; linear regression; robust statistics Číslo projektu: CEZ:AV0Z10300504 (CEP), GA402/09/0732 (CEP) Poskytovatel projektu: GA ČR Zdrojový dokument: International Days of Statistics and Economics, ISBN 978-80-86175-77-5