A Bayesian Model of COVID-19 Cases Based on the Gompertz Curve
نویسندگان
چکیده
The COVID-19 pandemic has highlighted the need for finding mathematical models to forecast evolution of contagious disease and evaluate success particular policies in reducing infections. In this work, we perform Bayesian inference a non-homogeneous Poisson process with an intensity function based on Gompertz curve. We discuss prior distribution parameter generate samples from posterior by using Markov Chain Monte Carlo (MCMC) methods. Finally, illustrate our method analyzing real data associated specific region located at south Spain.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2021
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math9030228