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Virology: Current Research

ISSN: 2736-657X

Open Access

Ba lin

Department of Mathematic and Statistics, Central China Normal University, Luoyu, Wuhan, 430071, Hubei, China

Publications
  • Research Article   
    Consistence Condition of Kernel Selection in Regular Linear Kernel Regression and Its Application in COVID-19 High-risk Areas Exploration
    Author(s): Lu xan* and Ba lin

    With the long-term outbreak of the COVID-19 around the world, identi- fying high-risk areas is becoming a new research boom. In this paper, we propose a novel regression method namely Regular Linear Kernel Regression (RLKR) for COVID-19 high-risk areas exploration. We explain in detail how the canonical linear kernel regression method is linked to the identification of high-risk areas for COVID-19. Furthermore, the consistence condition of Kernel Selection, which is closely related to the identification of high-risk areas, is given with two mild assumptions. Finally, the RLKR method was verified by simulation experiments and applied for COVID-19 high-risk area Exploration... Read More»
    DOI: 10.37421/2736-657X.07.2023.003

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