One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE.
作者： Lauren C. Ponisio , Perry Valpine , Nicholas Michaud , Daniel Turek
DOI: 10.1002/ECE3.6053
关键词: Bayesian probability 、 Hierarchical database model 、 Markov chain Monte Carlo 、 Univariate 、 Artificial intelligence 、 Structure (mathematical logic) 、 Sampling (statistics) 、 Machine learning 、 Software 、 Bayesian inference 、 Computer science
摘要: … hierarchical modeling in ecology, our results suggest that NIMBLE can be much more efficient than JAGS in the cases where it matters most, when overall efficiency is quite low. …
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