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Functional Principal Component Analysis of Spatio-Temporal Point Processes with Applications in Disease Surveillance
In disease surveillance applications, the disease events are modeled by spatio-temporal point processes. We propose a new class of semiparametric generalized linear mixed model for such data, where the event rate is related to some known risk factors and some unknown latent random effects. We model...
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| Glavni autori: | , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
2014
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| Teme: | |
| Online pristup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4215517/ https://ncbi.nlm.nih.gov/pubmed/25368436 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2014.885434 |
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