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- W1974916427 abstract "Markov chain Monte Carlo (MCMC) is a statistical innovation that allows researchers to fit far more com- plex models to data than is feasible using conventional methods. Despite its widespread use in a variety of scien- tific fields, MCMC appears to be underutilized in wildlife applications. This may be due to a misconception that MCMC requires the adoption of a subjective Bayesian analysis, or perhaps simply to its lack of familiarity among wildlife researchers. We introduce the basic ideas of MCMC and software BUGS (Bayesian inference using Gibbs sampling), stressing that a simple and satisfactory intuition for MCMC does not require extraordinary mathemat- ical sophistication. We illustrate the use of MCMC with an analysis of the association between latent factors gov- erning individual heterogeneity in breeding and survival rates of kittiwakes (Rissa tridactyla). We conclude with a discussion of the importance of individual heterogeneity for understanding population dynamics and designing management plans." @default.
- W1974916427 created "2016-06-24" @default.
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- W1974916427 date "2002-04-01" @default.
- W1974916427 modified "2023-10-16" @default.
- W1974916427 title "Of Bugs and Birds: Markov Chain Monte Carlo for Hierarchical Modeling in Wildlife Research" @default.
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- W1974916427 doi "https://doi.org/10.2307/3803160" @default.
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