Classical and robust orthogonal regression between parts of compositional data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F16%3A33159845" target="_blank" >RIV/61989592:15310/16:33159845 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1080/02331888.2016.1162164" target="_blank" >http://dx.doi.org/10.1080/02331888.2016.1162164</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/02331888.2016.1162164" target="_blank" >10.1080/02331888.2016.1162164</a>
Alternative languages
Result language
angličtina
Original language name
Classical and robust orthogonal regression between parts of compositional data
Original language description
The different parts (variables) of a compositional data set cannot be considered independent from each other, since only the ratios between the parts constitute the relevant information to be analysed. Practically, this information can be included in a system of orthonormal coordinates. For the task of regression of one part on other parts, a specific choice of orthonormal coordinates is proposed which allows for an interpretation of the regression parameters in terms of the original parts. In this context, orthogonal regression is appropriate since all compositional parts - also the explanatory variables - are measured with errors. Besides classical (least-squares based) parameter estimation, also robust estimation based on robust principal component analysis is employed. Statistical inference for the regression parameters is obtained by bootstrap; in the robust version the fast and robust bootstrap procedure is used. The methodology is illustrated with a data set from macroeconomics.
Czech name
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Czech description
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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
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Statistics : a journal of theoretical and applied statistics
ISSN
0233-1888
e-ISSN
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Volume of the periodical
50
Issue of the periodical within the volume
6
Country of publishing house
GB - UNITED KINGDOM
Number of pages
15
Pages from-to
1261-1275
UT code for WoS article
000385543000005
EID of the result in the Scopus database
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