Extreme value-based methods for modeling elk yearly movements

DOI10.1007/s13253-018-00342-2zbMath1426.62361OpenAlexW2901065945WikidataQ59382983 ScholiaQ59382983MaRDI QIDQ1722629

Paul C. Cross, Ephraim M. Hanks, Benjamin A. Shaby, Dhanushi A. Wijeyakulasuriya

Publication date: 18 February 2019

Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13253-018-00342-2

zbMATH Keywords

MCMCanimal movementheavy-tailedresource selectiondisease spread

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Statistics of extreme values; tail inference (62G32) Animal behavior (92D50)

Uses Software

• R
• raster
• evmix
• batchmeans

Cites Work

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• The pseudo-marginal approach for efficient Monte Carlo computations
• A flexible extreme value mixture model
• Agent-based inference for animal movement and selection
• Continuous-time discrete-space models for animal movement
• Bayesian analysis of extreme events with threshold estimation
• A General Framework for the Analysis of Animal Resource Selection from Telemetry Data
• The Bayesian Lasso
• Bayesian Measures of Model Complexity and Fit
• Strictly Proper Scoring Rules, Prediction, and Estimation

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