A Bootstrap Comparison of Robust Regression Estimators
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F22%3A00583572" target="_blank" >RIV/67985556:_____/22:00583572 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/22:00564518 RIV/67985556:_____/22:00564518
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
A Bootstrap Comparison of Robust Regression Estimators
Original language description
The ordinary least squares estimator in linear regression is well known to be highly vulnerable to the presence of outliers in the data and available robust statistical estimators represent more preferable alternatives.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA21-05325S" target="_blank" >GA21-05325S: Modern nonparametric methods in econometrics</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mathematical Methods in Economics 2022: Proceedings
ISBN
978-80-88064-62-6
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
161-167
Publisher name
College of Polytechnics Jihlava
Place of publication
Jihlava
Event location
Jihlava
Event date
Sep 7, 2022
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000936355000066