Last updated: 2020-04-27

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CLIMB’s output is effectively the posterior MCMC samples of the parameters of the normal mixture. These samples can be used for clustering/classification, visualizations, and statistical inference. Here, we show implementations of several of the analyses used in the CLIMB manuscript.

To be written…

Visualizing convergence

First, let’s load in the MCMC we briefly ran on simulated data in the running the MCMC section.

Clustering dimensions and observations

Merging groups

Testing for consistency