Selected article for: "posterior probability and prior probability"
Author: Viktor Stojkoski; Zoran Utkovski; Petar Jolakoski; Dragan Tevdovski; Ljupco Kocarev
Title: The socio-economic determinants of the coronavirus disease (COVID-19) pandemic
  • Document date: 2020_4_17
    • ID: 80zg1rdz_30
    Snippet: Determinants with strong evidence: (PIP > 0.5). The first group describes the determinants which have by far larger posterior inclusion probability than the prior one, and thus there is strong evidence to be included in the true model. We find two variables for which there is such evidence in explaining the coronavirus cases: population size and GDP per capita (p.c.). The population size is negatively related to the number of registered COVID-19 .....
    Document: Determinants with strong evidence: (PIP > 0.5). The first group describes the determinants which have by far larger posterior inclusion probability than the prior one, and thus there is strong evidence to be included in the true model. We find two variables for which there is such evidence in explaining the coronavirus cases: population size and GDP per capita (p.c.). The population size is negatively related to the number of registered COVID-19 cases per million population, whereas the GDP p.c. exhibits a positive effect on the same variable. In the situation of coronavirus deaths, however, only the GDP p.c. remains a strong predictor, with a positive magnitude.

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