<div class="csl-bib-body">
<div class="csl-entry">Rieser, C., & Filzmoser, P. (2021). Compositional trend filtering. <i>Annales Mathematicae et Informaticae</i>, <i>53</i>, 257–270. https://doi.org/10.33039/ami.2021.02.004</div>
</div>
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dc.identifier.issn
1787-5021
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/138300
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dc.description.abstract
Trend filtering is known as the technique for detecting piecewise linear trends in univariate time series. This technique is extended to the setting of compositional data, which are multivariate data where only the relative information is of importance. According to this, we formulate the problem and present a procedure how to efficiently solve it. To show the usefulness of this method, we consider the number of COVID-19 infections in several European countries in a chosen time period.
