期刊
BIOMETRICAL JOURNAL
卷 53, 期 4, 页码 543-556出版社
WILEY
DOI: 10.1002/bimj.201000250
关键词
Bacteria; Convergence; Ecology; Hierarchical model; Process model
资金
- Scottish Government Rural and Environment Research and Analysis Directorate (RERAD)
Process models specified by non-linear dynamic differential equations contain many parameters, which often must be inferred from a limited amount of data. We discuss a hierarchical Bayesian approach combining data from multiple related experiments in a meaningful way, which permits more powerful inference than treating each experiment as independent. The approach is illustrated with a simulation study and example data from experiments replicating the aspects of the human gut microbial ecosystem. A predictive model is obtained that contains prediction uncertainty caused by uncertainty in the parameters, and we extend the model to capture situations of interest that cannot easily be studied experimentally.
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