{
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  "Title": "A Bayesian Repulsive Biclustering Model for Periodontal Data",
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  "Description": "Simultaneously clusters the Periodontal diseases (PD)\npatients and their tooth sites after taking the patient- and\nsite-level covariates into consideration. 'BAREB' uses the\ndeterminantal point process (DPP) prior to induce diversity\namong different biclusters to facilitate parsimony and\ninterpretability. Essentially, 'BAREB' is a cluster-wise linear\nmodel based on Yuliang (2020) <doi:10.1002/sim.8536>.",
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  "Maintainer": "Qingyang Liu <rh8liuqy@gmail.com>",
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    {
      "page": "BAREB",
      "title": "The BAREB package: summary information",
      "topics": [
        "BAREB"
      ]
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      "title": "const",
      "topics": [
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    },
    {
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      "title": "The initial value of patient- and site-level covariates for simulation",
      "topics": [
        "Init"
      ]
    },
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      "topics": [
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      "topics": [
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      "title": "Function to update the number of site level clusters for one patient level cluster via RJMCMC, when there is no patient in this cluster",
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      "title": "The simulation truth",
      "topics": [
        "truth"
      ]
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      "title": "update_RJ",
      "topics": [
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      "topics": [
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      "topics": [
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