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Author: Perry Williams
Assistant Professor of Statistical Ecology at University of Nevada, Reno
Upcoming short course entitled “Introductory R” at The Wildlife Society annual meeting in Albuquerque, New Mexico
This workshop, aimed at new R users, provides an introduction to object manipulation, data visualization and analysis, and basic programming in R. The R computing environment is a free, flexible, and open-source tool for data management, visualization, and analysis. We will cover a broad spectrum of topics including: how to import and export data, data… Continue reading Upcoming short course entitled “Introductory R” at The Wildlife Society annual meeting in Albuquerque, New Mexico
Upcoming short course entitled “Spatio-temporal dynamic statistical modeling in practice”
Short course on spatio-temporal dynamic statistical modeling at the Western North American Region of the International Biometric Society. The course is scheduled for June 25th, in Santa Fe, New Mexico from 1-5 pm. The course will provide an overview spatio-temporal statistical modeling, efficient computation and implementation of ecological diffusion models, and embedding S-T dynamic models… Continue reading Upcoming short course entitled “Spatio-temporal dynamic statistical modeling in practice”
New manuscript accepted in Methods in Ecology and Evolution
Williams, P. J., M. B. Hooten, J. N. Womble, and M. R. Bower. In Press. Estimating occupancy and abundance using aerial images with imperfect detection. Methods in Ecology and Evolution 00:00–00. Summary: Species distribution and abundance are critical population characteristics for efficient management, conservation, and ecological insight. Point process models are a powerful tool for modeling distribution… Continue reading New manuscript accepted in Methods in Ecology and Evolution
Article in Outdoor News Bulletin on sea otter research
Outdoor News Bulletin
Topic contributed session accepted for Joint Statistical Meeting (JSM) 2017 in Baltimore.
Session titled: Statistical challenges and opportunities for supporting national ecological monitoring programs, and led by Dr. Kathi Irvine
New manuscript accepted in Ecology on using basis functions for modeling spatial and temporal autocorrelation
Hefley, T.J., K.M. Broms, B.M. Brost, F.E. Buderman, S. Kay, H.R. Scharf, J.R. Tipton, P.J. Williams, and M.B. Hooten. (In Press). The basis function approach to modeling autocorrelation in ecological data. Ecology. Abstract: Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for… Continue reading New manuscript accepted in Ecology on using basis functions for modeling spatial and temporal autocorrelation
New manuscript accepted in Ecological Modelling on methods for combining multiple objectives
Williams, P. J, and W. L. Kendall. 2017. A guide to multiobjective optimization for ecological problems. Ecological Modelling 343:54-67. Abstract: Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including… Continue reading New manuscript accepted in Ecological Modelling on methods for combining multiple objectives
New manuscript accepted in Ecology on spatio-temporal methods for estimating colonization dynamics
Williams, P. J., M. B. Hooten, J. N. Womble, G. G. Esslinger, M. R. Bower, and T. J. Hefley. In Press. An integrated data model to estimate spatio-temporal occupancy, abundance, and colonization dynamics. Ecology. Abstract: Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or… Continue reading New manuscript accepted in Ecology on spatio-temporal methods for estimating colonization dynamics
Statistical decision theory manuscript in print at Ecological Applications
Abstract: Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT… Continue reading Statistical decision theory manuscript in print at Ecological Applications