Applied Time-Series Analysis for Fisheries and Environmental Data
Course webpage, R packages, and book on our new webpage
Fish catch forecasting and R Workflow with RStudio
Course webpage, lectures, labs, and online book from a recent short course
My research is focused on stochastic processes and statistical models for complex multivariate, interacting systems. Much of what I do involves developing algorithms for fitting multivariate autoregressive state-space (MARSS) models to time-series data, which comes up in vector autoregressive state-space modeling, dynamic linear modeling, MAR(1) modeling, and dynamic factor analysis. I developed an EM algorithm for fitting a general constrained version of these models and develped the MARSS package for fitting such models. In my spare time, I’ve been working on predictive models of “multi-player” systems—I’ve been studying this with soccer match data. This is another application of my work on developing predictive models using ‘bad’ data.
I am part of a NWFSC research group working in the area of hierarchical modeling and inference. Group members include myself, Eric Ward, Mark Scheuerell, and Jim Thorson, along with their post-docs and students. We develop statistical methods for ecological problems and apply these to resource and endangered species management questions. We collaborate a lot with folks at the University of Washington School for Aquatic and Fisheries Sciences (SAFS).
- Population Modeling
- Statistical Ecology
- Conservation Biology
- Time-series Analysis
- Stochastic Processes
- PhD in Zoology, 1995, University of Washington
- BS in Mechanical Engineering, 1988, Stanford University
- BS in Biology, 1988, Stanford University