Ordinal compositional data and time series
Publication date
2023-10-05
Document type
Forschungsartikel
Author
Organisational unit
Scopus ID
Publisher
Sage
Series or journal
Statistical Modelling
ISSN
Periodical volume
24
Periodical issue
6
First page
561
Last page
580
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Keyword
Compositional data
Conditional regression models
Control charts
Ordinal categories
Ordinal time series
Abstract
There are several real applications where the categories behind compositional data (CoDa) exhibit a natural order, which, however, is not accounted for by existing CoDa methods. For various application areas, it is demonstrated that appropriately developed methods for ordinal CoDa provide valuable additional insights and are, thus, recommended to complement existing CoDa methods. The potential benefits are demonstrated for the (visual) descriptive analysis of ordinal CoDa, for statistical inference based on CoDa samples, for the monitoring of CoDa processes by means of control charts, and for the analysis and modelling of compositional time series. The novel methods are illustrated by a couple of real-world data examples.
Description
This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Version
Published version
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