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COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning.
dc.contributor.author | Torres-Signes, Antoni | |
dc.contributor.author | Frías, María P. | |
dc.contributor.author | Ruiz-Medina, María D. | |
dc.date.accessioned | 2024-02-09T11:53:59Z | |
dc.date.available | 2024-02-09T11:53:59Z | |
dc.date.created | 2024 | |
dc.date.issued | 2021-03-19 | |
dc.identifier.citation | Torres–Signes, A., Frías, M.P. & Ruiz-Medina, M.D. COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning. Stoch Environ Res Risk Assess 35, 2659–2678 (2021). | es_ES |
dc.identifier.uri | https://hdl.handle.net/10630/30289 | |
dc.description.abstract | A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function is minimized in the framework of trigonometric regression. While, in our subsequent spatial residual correlation analysis, maximization of the likelihood allows us to compute the posterior mode in a Bayesian multivariate time series soft-data framework. The presented approach is applied to the analysis of COVID-19 mortality in the first wave affecting the Spanish Communities, since March 8, 2020 until May 13, 2020. An empirical comparative study with Machine Learning (ML) regression, based on random k-fold cross-validation, and bootstrapping confidence interval and probability density estimation, is carried out. This empirical analysis also investigates the performance of ML regression models in a hard- and soft-data frameworks. The results could be extrapolated to other counts, countries, and posterior COVID-19 waves. | es_ES |
dc.description.sponsorship | This work has been supported in part by projects PGC2018−099549-B-I00 of the Ministerio de Ciencia, Innovación y Universidades, Spain (co-funded with FEDER funds), and by grant A-FQM-345-UGR18 cofinanced by ERDF Operational Programme 2014-2020, and the Economy and Knowledge Council of the Regional Government of Andalusia, Spain. (In section Acknowledgements below, all sources of funding are also declared). | es_ES |
dc.language.iso | eng | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | COVID-19 - Mortalidad | es_ES |
dc.subject | Análisis de datos | |
dc.subject.other | COVID-19 analysis | es_ES |
dc.subject.other | Curve regression | es_ES |
dc.subject.other | Hard-data | es_ES |
dc.subject.other | Multivariate time series | es_ES |
dc.subject.other | Soft-data | es_ES |
dc.title | COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning. | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.identifier.doi | 10.1007/s00477-021-02021-0 | |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es_ES |