The BUGS project: Evolution, critique and future directions

Lunn, David J.; Spiegelhalter, David; Thomas, Andrew C.; Best, Nicky

doi:10.1002/sim.3680

Cited by 1,722 publications

(1,363 citation statements)

References 54 publications

(38 reference statements)

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“…Throughout this article, we use the general-purpose WinBUGS program (Lunn, Thomas, Best, & Spiegelhalter, 2000;Lunn, Spiegelhalter, Thomas, & Best, 2009; an introduction for psychologists is given by Sheu & O'Curry, 1998) that allows the user to specify and fit models without having to hand-code the MCMC algorithms. Although WinBUGS does not work for every application, it will work for most applications in the field of psychology.…”

Section: Bayesian Parameter Estimationmentioning

confidence: 99%

“…For most interesting models, this posterior is not available in closed-form, but instead has to be approximated by MCMC techniques. Fortunately, these MCMC techniques are implemented in the popular WinBUGS program (Lunn et al, 2000;Lunn et al, 2009;Ntzoufras, 2009); when using WinBUGS, all researchers have to do is to describe their model using an intuitive scripting language, and the details of the sampling process are automatically taken care of by WinBUGS (see Appendix B for examples). 2.…”

Section: Limitations Of the Savage-dickey Density Ratiomentioning

confidence: 99%

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Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method

Wagenmakers

Lodewyckx

Kuriyal

et al. 2010

Cognitive Psychology

639

642

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a b s t r a c tIn the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on statistical reporting. This is unfortunate, as the p-value provides at best a rough estimate of the evidence that the data provide for the presence of an experimental effect. An alternative and arguably more appropriate measure of evidence is conveyed by a Bayesian hypothesis test, which prefers the model with the highest average likelihood. One of the main problems with this Bayesian hypothesis test, however, is that it often requires relatively sophisticated numerical methods for its computation. Here we draw attention to the Savage-Dickey density ratio method, a method that can be used to compute the result of a Bayesian hypothesis test for nested models and under certain plausible restrictions on the parameter priors. Practical examples demonstrate the method's validity, generality, and flexibility.

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Section: Bayesian Parameter Estimationmentioning

confidence: 99%

Section: Limitations Of the Savage-dickey Density Ratiomentioning

confidence: 99%

Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method

Wagenmakers

Lodewyckx

Kuriyal

et al. 2010

Cognitive Psychology

639

642

View full text Add to dashboard Cite

show abstract

“…The multispecies approach retains the identity of encountered species throughout the modeling process and allows estimation of species-specific detection and occupancy probabilities, which can be derived from general or group-specific (e.g., taxonomic or functional) covariates [42,56]. Currently MSOMs must be written by the user and run within a programming environment or precompiled Markov chain Monte Carlo (MCMC) programs such as WinBUGS [57], Jags [58], or OpenBUGS [59], all of which use the Bayesian inference Using Gibbs Sampling (BUGS) language. Statistical programs such as R (http:// www.R-project.org) can often interface with MCMC programs.…”

Section: Richness and Diversity Estimation In The Multispecies Detectmentioning

confidence: 99%

Detecting diversity: emerging methods to estimate species diversity

Iknayan

Tingley

Furnas

et al. 2014

Trends in Ecology & Evolution

291

393

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“…The BBS count data were modeled as overdispersed Poisson variables and hierarchical Bayesian models were fit using Markov Chain Monte Carlo methods in JAGS (Lunn, Spiegelhalter, Thomas, & Best, 2009) implemented through R with package rjags (Plummer, 2016). With the exception of the budworm defoliation covariates, the model is very similar to the first difference model described in Link and Sauer (2016).…”

Section: Methodsmentioning

confidence: 99%

Cross‐scale effects of spruce budworm outbreaks on boreal warblers in eastern Canada

Drever

Smith

Venier

et al. 2018

Ecology and Evolution

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Insect outbreaks are major natural disturbance events that affect communities of forest birds, either directly by affecting the food supply or indirectly by changing the vegetation composition of forest canopies. An examination of correlations between measures of bird and insect abundance across different spatial scales and over varying time lag effects may provide insight into underlying mechanisms. We developed a hierarchical Bayesian model to assess correlations between counts of eight warbler species from the Breeding Bird Survey in eastern Canada, 1966 to 2009, with the presence of spruce budworm (Choristoneura fumiferana Clem.) at immediate local scales and time‐lagged regional scales, as measured by extent of defoliation on host tree species. Budworm‐associated species Cape May warbler (Setophaga tigrina), bay‐breasted warbler (Setophaga castanea), and Tennessee warbler (Oreothlypis peregrina) responded strongly and positively to both local and regional effects. In contrast, non‐budworm‐associated species, Blackburnian warbler (Setophaga fusca), magnolia warbler (Setophaga magnolia), Canada warbler (Cardellina canadensis), black‐throated blue warbler (Setophaga caerulescens), and black‐throated green warbler (Setophaga virens), only responded to regional effects in a manner that varied across eastern Canada. The complex responses by forest birds to insect outbreaks involve both increased numerical responses to food supply and to longer term responses to changes in forest structure and composition. These effects can vary across spatial scales and be captured in hierarchical population models, which can serve to disentangle common trends from data when examining drivers of population dynamics like forest management or climate change.

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The BUGS project: Evolution, critique and future directions

Cited by 1,722 publications

References 54 publications

Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method

Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method

Detecting diversity: emerging methods to estimate species diversity

Cross‐scale effects of spruce budworm outbreaks on boreal warblers in eastern Canada

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