Citations refer to the original publication, not to a Scieee localized version.
Boullosa González, P., Garea Espejo, A., Area Carracedo, I. C., Nieto Roig, J. J., & Mira Pérez, J. (2022). Leveraging geographically distributed data for influenza and SARS-CoV-2 non-parametric forecasting. MDPI. https://doi.org/10.3390/math10142494
Boullosa González, Pablo, et al. Leveraging geographically distributed data for influenza and SARS-CoV-2 non-parametric forecasting. MDPI, 2022. https://doi.org/10.3390/math10142494.
Boullosa González, Pablo, Adrián Garea Espejo, Iván Carlos Area Carracedo, Juan José Nieto Roig, and Jorge Mira Pérez. Leveraging geographically distributed data for influenza and SARS-CoV-2 non-parametric forecasting. MDPI, 2022. https://doi.org/10.3390/math10142494.
Boullosa González, P. et al. (2022) Leveraging geographically distributed data for influenza and SARS-CoV-2 non-parametric forecasting. MDPI. Available at: https://doi.org/10.3390/math10142494.
P. Boullosa González, A. Garea Espejo, I. C. Area Carracedo, J. J. Nieto Roig, and J. Mira Pérez, “Leveraging geographically distributed data for influenza and SARS-CoV-2 non-parametric forecasting,” MDPI, 2022, doi: 10.3390/math10142494.
@misc{boullosagonzalez2022leveraging,
author = {Boullosa González, Pablo and Garea Espejo, Adrián and Area Carracedo, Iván Carlos and Nieto Roig, Juan José and Mira Pérez, Jorge},
title = {Leveraging geographically distributed data for influenza and SARS-CoV-2 non-parametric forecasting},
year = {2022},
publisher = {MDPI},
doi = {10.3390/math10142494},
url = {https://doi.org/10.3390/math10142494}
}
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