Résumé :
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In Models for Ecological Data, James Clark introduces ecologists to these modern methods in modelling and computation. Assuming only basic courses in calculus and statistics, the text introduces readers to basic maximum likelihood and then works up to more advanced topics in Bayesian modelling and computation. Clark covers both classical statistical approaches and powerful new computational tools and describes how complexity can motivate a shift from classical to Bayesian methods. Through an available lab manual, the book introduces readers to the practical work of data modelling and computation in the language R. Based on a successful course at Duke University and National Science Foundation-funded institutes on hierarchical modelling, Models for Ecological Data will enable ecologists and other environmental scientists to develop useful models that make sense of ecological data. * Consistent treatment from classical to modern Bayes * Underlying distribution theory to algorithm development * Many examples and applications * Does not assume statistical background * Extensive supporting appendixes * Accompanying lab manual in R
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