New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis pr
Hierarchical Modelling for the Environmental Sciences: Statistical Methods and Applications
✍ Scribed by James S. Clark, Alan Gelfand
- Publisher
- Oxford University Press
- Year
- 2006
- Tongue
- English
- Leaves
- 216
- Series
- Oxford Biology
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
New statistical tools are changing the ways in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for anyalsis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirement for a clear exposition of the methodology through to application for a range of environmental challenges.
✦ Subjects
Науки о Земле;Метеорология и климатология;Методы обработки метеорологических данных;
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