Original title:
On Exact Heteroscedasticity Testing for Robust Regression
Authors:
Kalina, Jan ; Peštová, Barbora Document type: Research reports
Year:
2016
Language:
eng Series:
Technical Report, volume: V-1242 Abstract:
The paper is devoted to the least weighted squares estimator, which is one of highly robust estimators for the linear regression model. Novel permutation tests of heteroscedasticity are proposed. Also the asymptotic behavior of the permutation test statistics of the Goldfeld-Quandt and Breusch-Pagan tests is investigated. A numerical experiment on real economic data is presented, which also shows how to perform a robust prediction model under heteroscedasticity.
Keywords:
diagnostic tools; heteroscedasticity; outliers; robust estimation; variance Project no.: GA13-01930S (CEP) Funding provider: GA ČR
Institution: Institute of Computer Science AS ČR
(web)
Document availability information: Fulltext is available in the digital repository of the Academy of Sciences. Original record: http://hdl.handle.net/11104/0265795