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  "Package": "bnmonitor",
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  "Title": "An Implementation of Sensitivity Analysis in Bayesian Networks",
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  "Authors@R": "c(\nperson(\"Manuele\", \"Leonelli\", email = \"manuele.leonelli@ie.edu\", role = c(\"aut\",\"cre\")),\nperson(\"Ramsiya\", \"Ramanathan\", email = \"ramsiya.ramanathan@studio.unibo.it\", role = \"aut\"),\nperson(\"Rachel\", \"Wilkerson\", email = \"R.L.Wilkerson@warwick.ac.uk\", role = \"aut\"))",
  "Description": "An implementation of sensitivity and robustness methods in\nBayesian networks in R. It includes methods to perform\nparameter variations via a variety of co-variation schemes, to\ncompute sensitivity functions and to quantify the dissimilarity\nof two Bayesian networks via distances and divergences. It\nfurther includes diagnostic methods to assess the goodness of\nfit of a Bayesian networks to data, including global, node and\nparent-child monitors. Reference: M. Leonelli, R. Ramanathan,\nR.L. Wilkerson (2022) <doi:10.1016/j.knosys.2023.110882>.",
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  "Repository": "https://manueleleonelli.r-universe.dev",
  "Date/Publication": "2024-09-30 10:19:03 UTC",
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  "Author": "Manuele Leonelli [aut, cre],\nRamsiya Ramanathan [aut],\nRachel Wilkerson [aut]",
  "Maintainer": "Manuele Leonelli <manuele.leonelli@ie.edu>",
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    "orderp_covar",
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    "proportional_covar",
    "psd_check",
    "row_covar_matrix",
    "sensitivity",
    "sensquery",
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    "seq_marg_monitor",
    "seq_pa_ch_monitor",
    "total_covar_matrix",
    "uniform_covar"
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      "table": true,
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    },
    {
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      "table": false,
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      "fields": [
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        "Economic",
        "Events",
        "Admission"
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      "table": true,
      "tojson": true
    },
    {
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      ],
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    },
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      "fields": [],
      "table": false,
      "tojson": false
    },
    {
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      "title": "Pima Indian Diabetes Data",
      "object": "diabetes",
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        "DIAB"
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      "rows": 392,
      "table": true,
      "tojson": true
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      "name": "fire_alarm",
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      "fields": [],
      "table": true,
      "tojson": false
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        "analysis",
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      "rows": 88,
      "table": true,
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    },
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        "bn.fit.dnet"
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      "fields": [],
      "table": true,
      "tojson": false
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    {
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      "table": false,
      "tojson": false
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      "class": [
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      "tojson": false
    },
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      "fields": [],
      "table": true,
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      "title": "Message for the User",
      "topics": [
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      "topics": [
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      "title": "Measures of asymmetric independence",
      "topics": [
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      "topics": [
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        "bn2gbn"
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    },
    {
      "page": "bnmonitor",
      "title": "bnmonitor: A package for sensitivity analysis and robustness in Bayesian networks",
      "topics": [
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        "cachexia_ci",
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        "cachexia_gbn",
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        "control_gbn"
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    },
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      "title": "Christchurch Health and Development Study",
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        "chds_bn",
        "chds_bn.fit"
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    },
    {
      "page": "covariance_var",
      "title": "Standard variation of the covariance matrix",
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    {
      "page": "covariation",
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      "topics": [
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        "orderp_covar",
        "proportional_covar",
        "uniform_covar"
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    {
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      "title": "Co-variation matrices",
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        "covariation_matrix",
        "partial_covar_matrix",
        "row_covar_matrix",
        "total_covar_matrix"
      ]
    },
    {
      "page": "diabetes",
      "title": "Pima Indian Diabetes Data",
      "topics": [
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    },
    {
      "page": "diameter",
      "title": "Diameters in a Bayesian network",
      "topics": [
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      ]
    },
    {
      "page": "dwi",
      "title": "Distance-weigthed influence",
      "topics": [
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    },
    {
      "page": "edge_strength",
      "title": "Strength of edges in a Bayesian network",
      "topics": [
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    },
    {
      "page": "ewi",
      "title": "Edge-weigthed influence",
      "topics": [
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      ]
    },
    {
      "page": "final_node_monitor",
      "title": "Final node monitors",
      "topics": [
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    },
    {
      "page": "fire_alarm",
      "title": "Bayesian network on fire alarm system",
      "topics": [
        "fire_alarm"
      ]
    },
    {
      "page": "Fro",
      "title": "Frobenius norm",
      "topics": [
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      ]
    },
    {
      "page": "Fro.CI",
      "title": "Frobenius norm for 'CI'",
      "topics": [
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    },
    {
      "page": "Fro.GBN",
      "title": "Frobenius norm for 'GBN'",
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    },
    {
      "page": "global_monitor",
      "title": "Global monitor",
      "topics": [
        "global_monitor"
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    },
    {
      "page": "influential_obs",
      "title": "Influential observations",
      "topics": [
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    },
    {
      "page": "Jeffreys",
      "title": "Jeffreys Divergence",
      "topics": [
        "Jeffreys"
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    },
    {
      "page": "Jeffreys.CI",
      "title": "Jeffreys Divergence for 'CI'",
      "topics": [
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    {
      "page": "Jeffreys.GBN",
      "title": "Jeffreys Divergence for 'GBN'",
      "topics": [
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    },
    {
      "page": "KL",
      "title": "KL Divergence",
      "topics": [
        "KL"
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    },
    {
      "page": "KL_bounds",
      "title": "Bounds for the KL-divergence",
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      "page": "KL.CI",
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      "page": "KL.GBN",
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      "page": "mathmarks",
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    {
      "page": "mean_var",
      "title": "Standard variation of the mean vector",
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    },
    {
      "page": "model_pres_cov",
      "title": "Model-Preserving co-variation",
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    {
      "page": "mutual_info",
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      "topics": [
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    {
      "page": "node_monitor",
      "title": "Node monitor",
      "topics": [
        "node_monitor"
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    },
    {
      "page": "plot",
      "title": "Plotting methods",
      "topics": [
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        "plot.CD",
        "plot.diameter",
        "plot.dwi",
        "plot.edgestrength",
        "plot.ewi",
        "plot.final_node_monitor",
        "plot.fro",
        "plot.influential_obs",
        "plot.jeffreys",
        "plot.kl",
        "plot.mutualinfo",
        "plot.node_monitor",
        "plot.sensitivity",
        "plot.seq_cond_monitor",
        "plot.seq_marg_monitor",
        "plot.seq_pa_ch_monitor"
      ]
    },
    {
      "page": "print",
      "title": "Printing methods",
      "topics": [
        "print",
        "print.CD",
        "print.diameter",
        "print.dwi",
        "print.ewi",
        "print.final_node_monitor",
        "print.fro",
        "print.jeffreys",
        "print.kl",
        "print.mutualinfo",
        "print.node_monitor",
        "print.sensitivity",
        "print.seq_cond_monitor",
        "print.seq_marg_monitor",
        "print.seq_pa_ch_monitor"
      ]
    },
    {
      "page": "psd_check",
      "title": "Check for positive semi-definiteness after a perturbation",
      "topics": [
        "psd_check",
        "psd_check.CI",
        "psd_check.GBN"
      ]
    },
    {
      "page": "sensitivity",
      "title": "Sensitivity function",
      "topics": [
        "sensitivity"
      ]
    },
    {
      "page": "sensquery",
      "title": "Sensitivity of probability query",
      "topics": [
        "sensquery"
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    },
    {
      "page": "seq_node_monitor",
      "title": "Sequential node monitors",
      "topics": [
        "seq_cond_monitor",
        "seq_marg_monitor",
        "seq_node_monitor"
      ]
    },
    {
      "page": "seq_pa_ch_monitor",
      "title": "Sequential parent-child node monitors",
      "topics": [
        "seq_pa_ch_monitor"
      ]
    },
    {
      "page": "synthetic_bn",
      "title": "A synthetic Bayesian network",
      "topics": [
        "synthetic_bn"
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    },
    {
      "page": "synthetic_cbn",
      "title": "A synthetic continuous Bayesian network",
      "topics": [
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        "synthetic_ci",
        "synthetic_gbn"
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    {
      "page": "travel",
      "title": "Bayesian network on travel survey",
      "topics": [
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