Now more than ever, statistical tool are being used to analyze and interpret data and models in the environmental sciences. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale.
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Now more than ever, statistical tool are being used to analyze and interpret data and models in the environmental sciences. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale.
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