ArticleResults in physics2021
Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea.
Article in Results in physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Exponentially Weighted Multivariate HAR Model with Applications in the Stock Market.Entropy (Basel, Switzerland) · 2022Article
- Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement.Chaos, solitons, and fractals · 2022Article
- Genomic Variations in the Structural Proteins of SARS-CoV-2 and Their Deleterious Impact on Pathogenesis: A Comparative Genomics Approach.Frontiers in cellular and infection microbiology · 2021Article
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Authors and funding
2 authors.
Funding
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Abstract
This paper deals with time series analysis for COVID-19 in South Korea. We adopt heterogeneous autoregressive (HAR) time series models and discuss the statistical inference for various COVID-19 data. Seven data sets such as cumulative confirmed (CC) case, cumulative recovered (CR) case and cumulative death (CD) case as well as recovery rate, fatality rate and infection rates for 14 and 21 days are handled for the statistical analysis. In the HAR models, model selections of orders are conducted by evaluating root mean square error (RMSE) and mean absolute error (MAE) as well as
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