A Boosting-based Quantile Autoregressive Tree Model for the COVID-19 Time Series
Academic Paper from the year 2020 in the subject Computer Science - Applied, grade: A, , language: English, abstract: Analysis and modelling of the daily observations is of the interest for both academic and practical needs during the worst public health crisis in decades. In this paper we propose a Boosting-based Quantile Autoregressive Tree (BQART) model to estimate the evolution in reported cases and fatality of the COVID-19 pandemic. The proposed approach benefit from the boosting methodology and the additive quantile regression to overcome challenges of unknown probabilistic distribution in the autoregressive variable and location shift…
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Produktdetails
- ISBN: 978-3-346-24494-9
- EAN: 9783346244949
- Produktnummer: 34711984
- Verlag: Grin Verlag
- Sprache: Englisch
- Erscheinungsjahr: 2020
- Seitenangabe: 23 S.
- Plattform: PDF
- Masse: 1'422 KB
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