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Exploratory data analysis for interval compositional data
Authors
A Alfons
A Chouakria
+41 more
C Lauro
D Billheimer
DF Morrison
E Fišerová
EAL Neto
EAL Neto
EM Kroonenberg
EM Kroonenberg
G Mateu-Figueras
H Wang
I Kojadinovic
J Aitchison
J Aitchison
J Aitchison
J Palarea-Albaladejo
JJ Egozcue
JJ Egozcue
JJ Egozcue
Karel Hron
L Billard
M Noirhomme-Fraiture
MA Engle
ML Eaton
O Pavlačka
P Brito
P Cazes
P Filzmoser
P Filzmoser
P Filzmoser
P Filzmoser
P Filzmoser
P Teles
P Zuccolotto
Paula Brito
Peter Filzmoser
PJ Rousseeuw
R Bro
RE Moore
V Pawlowsky-Glahn
V Pawlowsky-Glahn
V Pawlowsky-Glahn
Publication date
1 January 2017
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
Compositional data are considered as data where relative contributions of parts on a whole, conveyed by (log-)ratios between them, are essential for the analysis. In Symbolic Data Analysis (SDA), we are in the framework of interval data when elements are characterized by variables whose values are intervals on (Formula presented.) representing inherent variability. In this paper, we address the special problem of the analysis of interval compositions, i.e., when the interval data are obtained by the aggregation of compositions. It is assumed that the interval information is represented by the respective midpoints and ranges, and both sources of information are considered as compositions. In this context, we introduce the representation of interval data as three-way data. In the framework of the log-ratio approach from compositional data analysis, it is outlined how interval compositions can be treated in an exploratory context. The goal of the analysis is to represent the compositions by coordinates which are interpretable in terms of the original compositional parts. This is achieved by summarizing all relative information (logratios) about each part into one coordinate from the coordinate system. Based on an example from the European Union Statistics on Income and Living Conditions (EU-SILC), several possibilities for an exploratory data analysis approach for interval compositions are outlined and investigated. © 2016 Springer-Verlag Berlin Heidelber
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