111 citations
4 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 Linear Mixed Model Formulation for Spatio-Temporal Random Processes with Computational Advances for the Separable and Product-Sum Covariances
Michael Dumelle, Jay M. Ver Hoef, Claudio Fuentes +1
We describe spatio-temporal random processes using linear mixed models. We show how many commonly used models can be viewed as special cases of this general framework and pay close…
Tracking Live Fish from Low-Contrast and Low-Frame-Rate Stereo Videos
Meng-Che Chuang, Jenq-Neng Hwang, Kresimir Williams +1
Non-extractive fish abundance estimation with the aid of visual analysis has drawn increasing attention. Unstable illumination, ubiquitous noise and low frame rate video capturing…
Estimating Abundance from Counts in Large Data Sets of Irregularly-Spaced Plots using Spatial Basis Functions
Jay M. Ver Hoef, John K. Jansen
Monitoring plant and animal populations is an important goal for both academic research and management of natural resources. Successful management of populations often depends on o…