Rieser, Christopher and Filzmoser, Peter (2021) Compositional trend filtering. Annales Mathematicae et Informaticae, 53. pp. 257-270. ISSN 1787-6117
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Official URL: https://doi.org/10.33039/ami.2021.02.004
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.
| Item Type: | Article |
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| Uncontrolled Keywords: | Trend filtering, compositional data, COVID-19 |
| Subjects: | Q Science / természettudomány > QA Mathematics / matematika > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány |
| Depositing User: | Tibor Gál |
| Date Deposited: | 25 May 2021 10:10 |
| Last Modified: | 25 May 2021 10:10 |
| URI: | http://real.mtak.hu/id/eprint/125749 |
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