Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves

08/20/2020
by   Tianyu Pan, et al.
0

We study the spatial heterogeneity effect on regional COVID-19 pandemic timing and severity by analyzing the COVID-19 growth rate curves in the United States. We propose a geographically detailed functional data grouping method equipped with a functional conditional autoregressive (CAR) prior to fully capture the spatial correlation in the pandemic curves. The spatial homogeneity pattern can then be detected by a geographically weighted Chinese restaurant process prior which allows both locally spatially contiguous groups and globally discontiguous groups. We design an efficient Markov chain Monte Carlo (MCMC) algorithm to simultaneously infer the posterior distributions of the number of groups and the grouping configuration of spatial functional data. The superior numerical performance of the proposed method over competing methods is demonstrated using simulated studies and an application to COVID-19 state-level and county-level data study in the United States.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 18

page 24

02/16/2020

Bayesian Spatial Homogeneity Pursuit of Functional Data: an Application to the U.S. Income Distribution

An income distribution describes how an entity's total wealth is distrib...
08/10/2020

Time Fused Coefficient SIR Model with Application to COVID-19 Epidemic in the United States

In this paper, we propose a Susceptible-Infected-Removal (SIR) model wit...
03/06/2020

Bayesian Spatial Homogeneity Pursuit for Survival Data with an Application to the SEER Respiration Cancer

In this work, we propose a new Bayesian spatial homogeneity pursuit meth...
07/16/2020

Heterogeneity Learning for SIRS model: an Application to the COVID-19

We propose a Bayesian Heterogeneity Learning approach for Susceptible-In...
03/23/2020

Heterogeneity Pursuit for Spatial Point Pattern with Application to Tree Locations: A Bayesian Semiparametric Recourse

Spatial point pattern data are routinely encountered. A flexible regress...
03/16/2021

Identification of COVID-19 mortality patterns in Brazil by a functional QR decomposition analysis

This paper introduces a functional extension of the QR decomposition of ...
01/08/2022

Bayesian Changepoint Estimation for Spatially Indexed Functional Time Series

We propose a Bayesian hierarchical model to simultaneously estimate mean...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.