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Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram.
Gonçalves, Alan D S; Fernandes, Leonardo H S; Nascimento, Abraão D C.
Afiliação
  • Gonçalves ADS; Departamento de Estatssca, Universidade Federal de Pernambuco, Recife, PE, 50670-901, Brazil.
  • Fernandes LHS; Department of Economics and Informatics, Federal Rural University of Pernambuco, Serra Talhada, PE, 56909-535, Brazil.
  • Nascimento ADC; Departamento de Estatssca, Universidade Federal de Pernambuco, Recife, PE, 50670-901, Brazil.
Chaos Solitons Fractals ; 164: 112634, 2022 Nov.
Article em En | MEDLINE | ID: mdl-36118941
The pandemic COVID-19 brings with it the need for studies and tools to help those in charge make decisions. Working with classical time series methods such as ARIMA and SARIMA has shown promising results in the first studies of COVID-19. We advance in this branch by proposing a risk factor map induced by the well-known Pearson diagram based on multivariate kurtosis and skewness measures to analyze the dynamics of deaths from COVID-19. In particular, we combine bootstrap for time series with SARIMA modeling in a new paradigm to construct a map on which one can analyze the dynamics of a set of time series. The proposed map allows a risk analysis of multiple countries in the four different periods of the pandemic COVID-19 in 55 countries. Our empirical evidence suggests a direct relationship between the multivariate skewness and kurtosis. We observe that the multivariate kurtosis increase leads to the rise of the multivariate skewness. Our findings reveal that the countries with high risk from the behavior of the number of deaths tend to have pronounced skewness and kurtosis values.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Chaos Solitons Fractals Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Chaos Solitons Fractals Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido