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This repository has been archived by the owner on Jan 12, 2020. It is now read-only.
As discussed the other day - these are the underlying problems here:
Introducing noise to the Q-estimates (which the code in previous commit does do.)
Introducing noise in the label switches
Changing Dirichlet params to introduce multiple modes.
The suggestion by Melanie to solve 2. is to pass a confusion matrix as input for a sample being mislabelled. i.e. say we have a Q-matrix with correct labels then in each replicate we add noise to the Q and swap labels with some probability given by the confusion matrix.
Alternatively
The label.switching package has a function called permute.mcmc that I think does what we want.
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see http://www.cs.cmu.edu/~epxing/Class/10701-08s/recitation/dirichlet.pdf and
https://en.wikipedia.org/wiki/Dirichlet_distribution
Will have to fix labelling at some point but it is a start.
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