Original title: On Heteroscedasticity in Robust Regression
Authors: Kalina, Jan
Document type: Papers
Conference/Event: International Days of Statistics and Economics /5./, Prague (CZ), 2011-09-22 / 2011-09-23
Year: 2011
Language: eng
Abstract: 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.
Keywords: diagnostics; linear regression; robust statistics
Project no.: CEZ:AV0Z10300504 (CEP), GA402/09/0732 (CEP)
Funding provider: GA ČR
Host item entry: International Days of Statistics and Economics, ISBN 978-80-86175-77-5

Institution: Institute of Computer Science AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://msed.vse.cz/files/2011/Kalina.pdf
Original record: http://hdl.handle.net/11104/0205068

Permalink: http://www.nusl.cz/ntk/nusl-81269


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Research > Institutes ASCR > Institute of Computer Science
Conference materials > Papers