Author: Sofia Morfopoulou; Vincent Plagnol
Title: Bayesian mixture analysis for metagenomic community profiling. Document date: 2014_7_25
ID: 058r9486_66
Snippet: Each combination of species corresponds to a finite mixture model for which the marginal likelihood can be estimated. Marginal likelihood comparison has a central role in comparing different models {M 1 , . . . , M m }. To compute the marginal likelihood P (X|M k ) for the mixture model M k one has to average over the parameters with respect to the prior distribution π(θ k |M k ), where θ k are the model parameters:.....
Document: Each combination of species corresponds to a finite mixture model for which the marginal likelihood can be estimated. Marginal likelihood comparison has a central role in comparing different models {M 1 , . . . , M m }. To compute the marginal likelihood P (X|M k ) for the mixture model M k one has to average over the parameters with respect to the prior distribution π(θ k |M k ), where θ k are the model parameters:
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