Diagnostics for Robust Regression: Linear Versus Nonlinear Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00467762" target="_blank" >RIV/67985807:_____/16:00467762 - isvavai.cz</a>
Result on the web
<a href="https://msed.vse.cz/msed_2016/article/3-Kalina-Jan-paper.pdf" target="_blank" >https://msed.vse.cz/msed_2016/article/3-Kalina-Jan-paper.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Diagnostics for Robust Regression: Linear Versus Nonlinear Model
Original language description
Robust statistical methods represent important tools for estimating parameters in linear as well as nonlinear econometric models. In contrary to the least squares, they do not suffer from vulnerability to the presence of outlying measurements in the data. Nevertheless, they need to be accompanied by diagnostic tools for verifying their assumptions. In this paper, we propose the asymptotic Goldfeld-Quandt test for the regression median. It allows to formulate a natural procedure for models with heteroscedastic disturbances, which is again based on the regression median. Further, we pay attention to nonlinear regression model. We focus on the nonlinear least weighted squares estimator, which is one of recently proposed robust estimators of parameters in a nonlinear regression. We study residuals of the estimator and use a numerical simulation to reveal that they can be severely heteroscedastic also for data generated from a model with homoscedastic disturbances. Thus, we give a warning that standard residuals of the robust nonlinear estimator may produce misleading results if used for the standard diagnostic tools
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The 10th International Days of Statistics and Economics Conference Proceedings
ISBN
978-80-87990-10-0
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
781-790
Publisher name
MELANDRIUM
Place of publication
Slaný
Event location
Prague
Event date
Dec 14, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000389515100077