Benjamin B Risk

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The incidence function model (IFM) uses area and connectivity to predict metapopulation dynamics. However, false absences and missing data can lead to underestimates of the number of sites contributing to connectivity, resulting in overestimates of dispersal ability and turnovers (extinctions plus colonizations). We extend estimation methods for the IFM by(More)
We examine differences between independent component analyses (ICAs) arising from different assumptions, measures of dependence, and starting points of the algorithms. ICA is a popular method with diverse applications including artifact removal in electrophysiology data, feature extraction in microarray data, and identifying brain networks in functional(More)
Estimating spatiotemporal models for multi-subject fMRI is computationally challenging. We propose a mixed model for localization studies with spatial random effects and time-series errors. We develop method-of-moment estimators that leverage population and spatial information and are scalable to massive datasets. In simulations, subject-specific estimates(More)
A.1 The Infomax algorithm We are not aware of functions or packages in R that implement the Infomax algorithm (Bell and Sejnowski 1995). We offer an alternative to Matlab code (http://cnl.salk. edu/ ~ tewon/ICA/code.html), but with a few modifications that decrease computation time. First, we use the full data (the so-called offline algorithm) in each(More)
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