Markov chain Monte Carlo

State-space models for ecological time-series data: Practical model-fitting
State-space models are an increasingly common and important tool in the quantitative ecologists’ armoury, particularly for the analysis …
Ken Newman, Ruth King, Víctor Elvira, Perry de Valpine, Rachel S. McCrea, Byron J. T. Morgan
Last updated on Jun 9, 2022
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Efficient estimation of large-scale spatial capture–recapture models
Capture–recapture methods are a common tool in ecological statistics, which have been extended to spatial capture–recapture models for …
Daniel Turek, Cyril Milleret, Torbjørn Ergon, Henrik Brøseth, Pierre Dupont, Richard Bischof, Perry de Valpine
Last updated on Jun 8, 2022
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One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE
Improved efficiency of Markov chain Monte Carlo facilitates all aspects of statistical analysis with Bayesian hierarchical models. …
Lauren C. Ponisio, Perry de Valpine, Nicholas Michaud, Daniel Turek
Last updated on Jun 8, 2022
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Estimating tree growth from complex forest monitoring data
Understanding tree growth as a function of tree size is important for a multitude of ecological and management applications. …
Melissa Eitzel, John Battles, Robert York, Jonas Knape, Perry de Valpine
Last updated on Jun 8, 2022
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Population dynamics of an Arctiid caterpillar–tachinid parasitoid system using state-space models
  1. Population dynamics of insect host–parasitoid systems are important in many natural and managed ecosystems and have inspired much …
Richard Karban, Perry de Valpine
Last updated on Jun 8, 2022
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Field-Scale Roles of Density, Temperature, Nitrogen, and Predation on Aphid Population Dynamics
Robust analyses of noisy, stage-structured, irregularly spaced, field-scale data incorporating multiple sources of variability and …
Perry de Valpine, Jay A. Rosenheim
Last updated on Jun 8, 2022
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