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  "Description": "Model data with a suspected clustering structure (either\nin co-variate space, regression space or both) using a Bayesian\nproduct model with a logistic regression likelihood.\nObservations are represented graphically and clusters are\nformed through various edge removals or additions. Cluster\nquality is assessed through the log Bayesian evidence of the\noverall model, which is estimated using either a Sequential\nMonte Carlo sampler or a suitable transformation of the\nBayesian Information Criterion as a fast approximation of the\nformer. The internal Iterated Batch Importance Sampling scheme\n(Chopin (2002 <doi:10.1093/biomet/89.3.539>)) is made available\nas a free standing function.",
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      "title": "Utilising Normalisation Constant Optimisation Via Edge Removal",
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