1 citations · 2 across the 7 of their papers we have counts for
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Composition as Direction: An Active-Set Ray-Based Model for Sparse High-Dimensional Compositional Data
Michael R Schwob, Jyotishka Datta
[Working Draft] Compositional data are central to microbial, ecological, and environmental research, yet often have four features that are difficult to accommodate jointly: exact z…
Spatial Hyperspheric Models for Compositional Data
Michael R. Schwob, Mevin B. Hooten, Nicholas M. Calzada +1
Compositional observations are an increasingly prevalent data source in spatial statistics. Analysis of such data is typically done on log-ratio transformations or via Dirichlet re…
Composite Dyadic Models for Spatio-Temporal Data
Michael R Schwob, Mevin B Hooten, Vagheesh Narasimhan
Mechanistic statistical models are commonly used to study the flow of biological processes. For example, in landscape genetics, the aim is to infer spatial mechanisms that govern g…
Geostatistical capture-recapture models
Mevin B Hooten, Michael R Schwob, Devin S Johnson +1
Methods for population estimation and inference have evolved over the past decade to allow for the incorporation of spatial information when using capture-recapture study designs.…
Dynamic Population Models with Temporal Preferential Sampling to Infer Phenology
Michael R. Schwob, Mevin B. Hooten, Travis McDevitt-Galles
To study population dynamics, ecologists and wildlife biologists use relative abundance data, which are often subject to temporal preferential sampling. Temporal preferential sampl…
Multistage Hierarchical Capture-Recapture Models
Mevin B Hooten, Michael R Schwob, Devin S Johnson +1
Ecologists increasingly rely on Bayesian methods to fit capture-recapture models. Capture-recapture models are used to estimate abundance while accounting for imperfect detectabili…