Download PDFOpen PDF in browserAutomatic covariates selection in dynamic regression models with application to COVID-19 evolution3 pages•Published: February 16, 2023AbstractThis work introduces a new approach in time-series analysis field for automatic co- variates selection in dynamic regression models. Based on [1] and [2] previous study, a forward-selection method is proposed for adding new significant covariates from a given set. This algorithm has been implemented and optimized in R as a package, and it has been applied to multiple simulations to validate its performance. Finally, the obtained results from the IRAS database of Catalonia are presented to analyze the COVID-19 evolution.Keyphrases: data science, dynamic regression models, time series analysis In: Alvaro Leitao and Lucía Ramos (editors). Proceedings of V XoveTIC Conference. XoveTIC 2022, vol 14, pages 136-138.
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