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Spatiotemporal Prediction of COVID-19 Mortality and Risk Assessment
This paper presents a multivariate functional data statistical approach, for spatiotemporal prediction of COVID-19 mortality counts. Specifically, spatial heterogeneous nonlinear parametric functional regression trend model fitting is first implemented. Classical and Bayesian infinite-dimensional log-Gaussian linear residual correlation analysis is then applied. The nonlinear regression predictor of the mortality risk is combined with the plug-in predictor of the multiplicative error term. Andoi:10.21203/rs.3.rs-56955/v1 fatcat:tmkxfsmz7bccdbuqacl2qft7q4