Number of the records: 1  

Kernel density estimation for circular data about COVID-19 in the Czech Republic

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    SYSNO ASEP0544804
    Document TypeA - Abstract
    R&D Document TypeThe record was not marked in the RIV
    R&D Document TypeNení vybrán druh dokumentu
    TitleKernel density estimation for circular data about COVID-19 in the Czech Republic
    Author(s) Katina, Stanislav (UIVT-O) SAI, ORCID, RID
    Zámečník, S. (CZ)
    Hórová, I. (CZ)
    Number of authors3
    Source TitleISCB 2021: 42nd Annual Conference of the International Society for Biostatistics: Final Programme & Book of Abstracts. - Lyon : ISCB / University Lyon, 2021
    S. 244-244
    Number of pages1 s.
    ActionISCB 2021: Annual Conference of the International Society for Biostatistics /42./
    Event date18.07.2021 - 22.07.2021
    VEvent locationLyon
    CountryFR - France
    Event typeWRD
    Languageeng - English
    CountryFR - France
    Institutional supportUIVT-O - RVO:67985807
    AnnotationThe term circular statistics describes a set of techniques used to model distributions of random variables that are cyclic in nature and these approaches can be easily adapted to temporal data recorded, e.g., daily, weekly or monthly. One of the nonparametric possibilities how to analyze these data is through kernel estimations of circular densities where the problem of how much to smooth, i.e., how to choose the bandwidth, is crucial. In this presentation we describe the existing methods: cross-validation method, smoothed cross-validation, adaptive method and propose their modifications. We apply these methods on real data from the Institute of health information and statistics of the Czech Republic about total (cumulative) number of persons with a proven COVID-19 infection according to regional hygienic stations, number of cured persons, number of deaths and tests performed for whole country and regions coded based on nomenclature of territorial units for Statistics (NUTS). The results are visualized as circular histograms (rose diagrams) and calculated standardized characteristics are superimposed with choropleth map, where NUTS are shaded in diverging color scheme. All statistical analyses are performed in the R software.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2022
Number of the records: 1  

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