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

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About: Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves
Creator	Hu, Guanyu Pan, Tianyu Shen, Weining
Source	ArXiv
abstract	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.
has issue date	2020-08-20(xsd:dateTime)
has license	arxiv
sha1sum (hex)	6a418006c507674926aa08f638eeb338cad42bb5
resource representing a document's title	Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves
resource representing a document's body	covid:6a418006c507674926aa08f638eeb338cad42bb5#body_text
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