Time Series Regression Models for COVID-19 Deaths

نویسندگان

چکیده

This article develops nonlinear functional forms for modeling count time series of daily deaths due to the COVID-19 virus. Our models explain mean levels while accounting time-varying variances. A Bayesian approach using Markov chain Monte Carlo (MCMC) is adopted analysis, inference and forecasting under proposed models. Applications are shown death counts from several countries affected by pandemic.

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ژورنال

عنوان ژورنال: Journal of data science

سال: 2021

ISSN: ['1680-743X', '1683-8602']

DOI: https://doi.org/10.6339/21-jds991