Time varying Markov process with partially observed aggregate data: an application to coronavirus

DOI10.1016/j.jeconom.2020.09.007OpenAlexW3110351285WikidataQ104101611 ScholiaQ104101611MaRDI QIDQ2106387

Christian Gouriéroux, Joanna Jasiak

Publication date: 14 December 2022

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.04500

zbMATH Keywords

coronavirusMarkov processestimating equationspartial observabilitySIR modelinformation recoveryinfection rate

Mathematics Subject Classification ID

Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Related Items (1)

Mezcla de Gompertz para modelar la evolución de la dinámica del COVID-19

Cites Work

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• Robust extended Kalman filtering
• Percolation Processes: Lower Bounds for the Critical Probability
• Estimation of Time-Varying Markov Processes with Aggregate Data
• Generalized Estimating Equations

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