Modeling and forecasting the spread and death rate of coronavirus (COVID-19) in the world using time series models

DOI10.1016/j.chaos.2020.110151zbMath1495.92091OpenAlexW3045032099WikidataQ98656607 ScholiaQ98656607MaRDI QIDQ2123619

Mohammad Reza Mahmoudi, Kim-Hung Pho, Mohsen Maleki, Mohammad Hossein Heydari

Publication date: 14 April 2022

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2020.110151

zbMATH Keywords

forecastingtime series modelingCOVID-19coronavirusestwo pieces scale mixtures of normal distributions

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Epidemiology (92D30)

Related Items (6)

A Bayesian approach on the two-piece scale mixtures of normal homoscedastic nonlinear regression models ⋮ Financial network connectedness and systemic risk during the COVID-19 pandemic ⋮ A simulation study of the COVID-19 pandemic based on the Ornstein-Uhlenbeck processes ⋮ SKEWED AUTO-REGRESSIVE PROCESS WITH EXOGENOUS INPUT VARIABLES: AN APPLICATION IN THE ADMINISTERED VACCINE DOSES ON COVID-19 SPREAD ⋮ Mathematical optimization models for reallocating and sharing health equipment in pandemic situations ⋮ Heteroscedastic nonlinear regression models using asymmetric and heavy tailed two-piece distributions

Uses Software

• itsmr

Cites Work

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