On Heteroscedasticity in Robust Regression

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00371587" target="_blank" >RIV/67985807:_____/11:00371587 - isvavai.cz</a>
Result on the web
<a href="http://msed.vse.cz/files/2011/Kalina.pdf" target="_blank" >http://msed.vse.cz/files/2011/Kalina.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
On Heteroscedasticity in Robust Regression
Original language description
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 priorknowledge 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.
Czech name
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Czech description
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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