Functional Principal Component Analysis of Spatiotemporal Point Processes With Applications in Disease Surveillance

DOI10.1080/01621459.2014.885434zbMath1368.62161OpenAlexW2043011098WikidataQ34432505 ScholiaQ34432505MaRDI QIDQ4975570

Yehua Li, Yongtao Guan

Publication date: 7 August 2017

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4215517

zbMATH Keywords

splinesstrong mixingsemiparametric methodscomposite likelihoodfunctional datalatent processspatiotemporal data

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Factor analysis and principal components; correspondence analysis (62H25) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Non-Markovian processes: estimation (62M09) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

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