Bayesian latent variable models for hierarchical clustered count outcomes with repeated measures in microbiome studies
Sign Up to like & getrecommendations! Published in 2017 at "Genetic Epidemiology"
DOI: 10.1002/gepi.22031
Abstract: Motivated by the multivariate nature of microbiome data with hierarchical taxonomic clusters, counts that are often skewed and zero inflated, and repeated measures, we propose a Bayesian latent variable methodology to jointly model multiple operational… read more here.
Keywords: models hierarchical; variable models; bayesian latent; repeated measures ... See more keywords
Nonuniversal power-law dynamics of susceptible infected recovered models on hierarchical modular networks.
Sign Up to like & getrecommendations! Published in 2021 at "Physical review. E"
DOI: 10.1103/physreve.103.062112
Abstract: Power-law (PL) time-dependent infection growth has been reported in many COVID-19 statistics. In simple susceptible infected recovered (SIR) models, the number of infections grows at the outbreak as I(t)∝t^{d-1} on d-dimensional Euclidean lattices in the… read more here.
Keywords: models hierarchical; modular networks; susceptible infected; infected recovered ... See more keywords