424 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Oceanic and Atmospheric AdministrationUS6 papers
- NOAA National Marine Fisheries ServiceUS5 papers
- Colorado State UniversityUS4 papers
- United States Geological SurveyUS4 papers
- NOAA National Marine Fisheries Service Southwest Fisheries Science CenterUS2 papers
- Oregon Department of Fish and WildlifeUS2 papers
- University of WashingtonUS2 papers
- Environmental Protection AgencyUS1 paper
- Iowa State UniversityUS1 paper
- National Park ServiceUS1 paper
- Oregon State UniversityUS1 paper
- United States Fish and Wildlife ServiceUS1 paper
11 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…
momentuHMM: R package for generalized hidden Markov models of animal movement
Brett T. McClintock, Theo Michelot
Discrete-time hidden Markov models (HMMs) have become an immensely popular tool for inferring latent animal behaviors from telemetry data. Here we introduce an open-source R packag…
Imputation Approaches for Animal Movement Modeling
Henry R. Scharf, Mevin B. Hooten, Devin S. Johnson
The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to prope…
Process convolution approaches for modeling interacting trajectories
Henry R. Scharf, Mevin B. Hooten, Devin S. Johnson +1
Gaussian processes are a fundamental statistical tool used in a wide range of applications. In the spatio-temporal setting, several families of covariance functions exist to accomm…
A Feature Learning and Object Recognition Framework for Underwater Fish Images
Meng-Che Chuang, Jenq-Neng Hwang, Kresimir Williams
Live fish recognition is one of the most crucial elements of fisheries survey applications where vast amount of data are rapidly acquired. Different from general scenarios, challen…
Basis Function Models for Animal Movement
Mevin B. Hooten, Devin S. Johnson
Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-ba…
Dynamic social networks based on movement
Henry R. Scharf, Mevin B. Hooten, Bailey K. Fosdick +3
Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect a…
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 demographic parameters using a combination of known-fate and open N-mixture models
Joshua H. Schmidt, Devin S. Johnson, Mark S. Lindberg +1
1. Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Recently developed N-mixture models use co…
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…