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|a 10.1080/02664763.2021.1936467
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|a eng
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|a Yang, Hou-Cheng
|e verfasserin
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|a Time fused coefficient SIR model with application to COVID-19 epidemic in the United States
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|c 2023
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 22.09.2024
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|a published: Electronic-eCollection
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|a Citation Status PubMed-not-MEDLINE
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|a © 2021 Informa UK Limited, trading as Taylor & Francis Group.
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|a In this paper, we propose a Susceptible-Infected-Removal (SIR) model with time fused coefficients. In particular, our proposed model discovers the underlying time homogeneity pattern for the SIR model's transmission rate and removal rate via Bayesian shrinkage priors. MCMC sampling for the proposed method is facilitated by the nimble package in R. Extensive simulation studies are carried out to examine the empirical performance of the proposed methods. We further apply the proposed methodology to analyze different levels of COVID-19 data in the United States
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|a Journal Article
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|a 62P10
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|a MCMC
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|a Time fusion
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|a homogeneity pursuit
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|a infectious diseases
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| 650 |
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|a shrinkage prior
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| 700 |
1 |
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|a Xue, Yishu
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Pan, Yuqing
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liu, Qingyang
|e verfasserin
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| 700 |
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|a Hu, Guanyu
|e verfasserin
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|u http://dx.doi.org/10.1080/02664763.2021.1936467
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