Outlier detection by means of robust regression estimators for use in engineering science
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F09%3A10104241" target="_blank" >RIV/00216208:11320/09:10104241 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1631/jzus.A0820140" target="_blank" >http://dx.doi.org/10.1631/jzus.A0820140</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1631/jzus.A0820140" target="_blank" >10.1631/jzus.A0820140</a>
Alternative languages
Result language
angličtina
Original language name
Outlier detection by means of robust regression estimators for use in engineering science
Original language description
The paper compares the ability of different robust regression estimators to detect and classify outliers. Estimators with a high breakdown point are compared and conclusions are drawn for real engineering applications. The least trimmed squares estimatoris recommended for heavily contaminated data sets with outliers with a complicated multivariate structure.
Czech name
—
Czech description
—
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
—
Result continuities
Project
—
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Zhejiang University: Science A
ISSN
1673-565X
e-ISSN
—
Volume of the periodical
10
Issue of the periodical within the volume
6
Country of publishing house
CN - CHINA
Number of pages
13
Pages from-to
909-921
UT code for WoS article
000266497300017
EID of the result in the Scopus database
—