Selected Problems in Statistical Modelling of Metalurgical Processes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F19%3A10243591" target="_blank" >RIV/61989100:27360/19:10243591 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Selected Problems in Statistical Modelling of Metalurgical Processes
Original language description
The paper introduces three modifications of the classical regression analysis, and shows their practical application when the problem of multicollinearity, wrong data or heteroscedasticity must be tackled. Compared are the results obtained from the classical regression approach and the ones resulting from the ridge regression, generalized linear regression and robust regression. The results are illustrated for the case of modelling dependencies of mechanical properties of casts on their chemical composition.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
METAL 2019 : conference proceedings : peer reviewed : 28th International Conference on Metallurgy and Materials : May 22nd-24th 2019, Hotel Voronez I, Brno, Czech Republic, EU
ISBN
978-80-87294-92-5
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1844-1851
Publisher name
Tanger
Place of publication
Ostrava
Event location
Brno
Event date
May 22, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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