Classical and Robust Regression Analysis with Compositional Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73610053" target="_blank" >RIV/61989592:15310/21:73610053 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s11004-020-09895-w" target="_blank" >https://link.springer.com/article/10.1007/s11004-020-09895-w</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11004-020-09895-w" target="_blank" >10.1007/s11004-020-09895-w</a>
Alternative languages
Result language
angličtina
Original language name
Classical and Robust Regression Analysis with Compositional Data
Original language description
Compositional data carry their relevant information in the relationships (logratios) between the compositional parts. It is shown how this source of information can be used in regression modeling, where the composition could either form the response, or the explanatory part, or even both. An essential step to set up a regression model is the way how the composition(s) enter the model. Here, balance coordinates will be constructed that support an interpretation of the regression coefficients and allow for testing hypotheses of subcompositional independence. Both classical least-squares regression and robust MM regression are treated, and they are compared within different regression models at a real data set from a geochemical mapping project.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA19-01768S" target="_blank" >GA19-01768S: Separation of geochemical signals in sediments: application of advanced statistical methods on large geochemical datasets</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Mathematical Geosciences
ISSN
1874-8961
e-ISSN
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Volume of the periodical
53
Issue of the periodical within the volume
5
Country of publishing house
DE - GERMANY
Number of pages
36
Pages from-to
823-858
UT code for WoS article
000575745000001
EID of the result in the Scopus database
2-s2.0-85092154380