20 citations · 39 across the 4 of their papers we have counts for
5 papers
Marginal Inference for Hierarchical Generalized Linear Mixed Models with Patterned Covariance Matrices Using the Laplace Approximation
Jay M. Ver Hoef, Eryn Blagg, Michael Dumelle +3
Using a hierarchical construction, we develop methods for a wide and flexible class of models by taking a fully parametric approach to generalized linear mixed models with complex…
A Class of Spatially Correlated Self-Exciting Models
Nicholas J Clark, Philip M. Dixon
The statistical modeling of multivariate count data observed on a space-time lattice has generally focused on using a hierarchical modeling approach where space-time correlation st…
An Extended Laplace Approximation Method for Bayesian Inference of Self-Exciting Spatial-Temporal Models of Count Data
Nicholas J. Clark, Philip M. Dixon
Self-Exciting models are statistical models of count data where the probability of an event occurring is influenced by the history of the process. In particular, self-exciting spat…
Modeling and Estimation for Self-Exciting Spatio-Temporal Models of Terrorist Activity
Nicholas J. Clark, Philip M. Dixon
Spatio-temporal hierarchical modeling is an extremely attractive way to model the spread of crime or terrorism data over a given region, especially when the observations are counts…
Assessing the impacts of time to detection distribution assumptions on detection probability estimation
Adam Martin-Schwarze, Jarad Niemi, Philip Dixon
Abundance estimates from animal point-count surveys require accurate estimates of detection probabilities. The standard model for estimating detection from removal-sampled point-co…