Finally, the existence of multiple strains in pathogen populations complicates modeling inference about transmission dynamics.
This chapter introduces concepts of the superpopulation model, model-based inference, and model-design based (model-assisted) inferences.
Probabilistic-modeling topics such as graphical models, latent-variable models, inference (e.g., belief propagation), parameter learning.
Bartoń, K. MuMIn: Multi-Model Inference.
Bartoń, K. MuMIn: multi-model inference R package version 1.14.0 20155).
Multi-model inference (including null models) was estimated by ranked changes in AICc <378.
Burnham, K. & Anderson, A. Model selection and multi-model inference: a practical information-theoretic approach.
Supplementary Figure 3 Marker free lineage tracing and model inference for additional xenograft models.
Covers Bayesian data analysis--modeling, inference, computing, and model checking.
Burnham, K. P. & Anderson, D. R. Model-Selection and Multi-Model Inference: A Practical Information-Theoretic Approach (Springer, 2002).
Burnham, K. P. & Anderson, D. R. Model Selection and Multi-Model Inference: A Practical Information-Theoretic Approach (Springer, 2010).
