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  "Version": "1.0.8",
  "Date": "2026-07-13",
  "Title": "High-Dimensional Model Selection",
  "Authors@R": "c(person(given = \"David\", family = \"Rossell\", role = c(\"aut\", \"cre\"), email = \"rosselldavid@gmail.com\"), person(given = c(\"John\", \"D.\"), family = \"Cook\", role = \"ctb\"), person(given = \"Donatello\", family = \"Telesca\", role = \"aut\"), person(given = \"P.\", family = \"Roebuck\", role = \"ctb\"), person(given = \"Oriol\", family = \"Abril\", role = \"aut\"), person(given = \"Miquel\", family = \"Torrens\", role = \"aut\"), person(given = \"Peter\", family = \"Mueller\", role = \"ctb\"), person(given = \"William\", family = \"Hallahan\", role = \"ctb\"))",
  "Maintainer": "David Rossell <rosselldavid@gmail.com>",
  "biocViews": "",
  "Description": "Model selection and averaging for regression, generalized\nlinear models, generalized additive models, graphical models\nand mixtures, focusing on Bayesian model selection and\ninformation criteria (Bayesian information criterion etc.). See\nRossell (2025) <doi:10.5281/zenodo.17119597> (see the URL field\nbelow for its URL) for a hands-on book describing the methods,\nexamples and suggested citations if you use the package.",
  "License": "GPL (>= 2)",
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  "BugReports": "https://github.com/davidrusi/modelSelection/issues",
  "LazyLoad": "yes",
  "Collate": "AllClasses.R AllGenerics.R alapl.R bms_ortho.R cil.R cox.R\nderivatives_nlps.R distribs.R dmom.R eBayes.R gam.R ggm.R\ngreedyGLM.R infocriteria.R initParameters.R localnulltest.R\nmarginalLikelihood.R msPriorSpec.R modelsearch.R\nmodelSelection.R modelSelectionGLM.R mombf.R normaliwish.R\nnormmix.R postMode.R rmom.R RcppExports.R testfunction.R",
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  "Date/Publication": "2026-07-16 07:56:46 UTC",
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    "igprior",
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    "localnulltest_fda",
    "localnulltest_fda_givenknots",
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    "modelSelection",
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    "postSamples",
    "priorp2g",
    "qimom",
    "qmom",
    "ralapl",
    "rnlp",
    "rpostNIW",
    "unifPrior",
    "zellnerprior"
  ],
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      "title": "Priors on model space for variable selection problems",
      "topics": [
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        "binomPrior",
        "unifPrior"
      ]
    },
    {
      "page": "bestBIC",
      "title": "Model with best AIC, BIC, EBIC or other general information criteria (getIC)",
      "topics": [
        "bestAIC",
        "bestAIC_fast",
        "bestBIC",
        "bestBIC_fast",
        "bestEBIC",
        "bestEBIC_fast",
        "bestIC",
        "bestIC_fast"
      ]
    },
    {
      "page": "bfnormmix",
      "title": "Number of Normal mixture components under Normal-IW and Non-local priors",
      "topics": [
        "bfnormmix"
      ]
    },
    {
      "page": "cil",
      "title": "Treatment effect estimation for linear models via Confounder Importance Learning using non-local priors.",
      "topics": [
        "cil"
      ]
    },
    {
      "page": "dalapl",
      "title": "Density and random draws from the asymmetric Laplace distribution",
      "topics": [
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        "palapl",
        "ralapl"
      ]
    },
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      "title": "Dirichlet density",
      "topics": [
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    },
    {
      "page": "diwish",
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      "page": "dmom",
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        "demom,vector-method",
        "demom-methods",
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        "qimom",
        "qmom"
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    {
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      "topics": [
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        "rpostNIW"
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    },
    {
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        "icfit-class",
        "icfit.coef",
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        "icfit.summary",
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        "localnulltest_fda",
        "localnulltest_fda_givenknots",
        "localnulltest_givenknots"
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    {
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      "title": "Marginal (or integrated) likelihood density of the observed data for an individual model handled by modelSelection (regression, GLM, GAM, accelerated failure time, regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals",
      "topics": [
        "marginalLikelihood"
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    },
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      "title": "Marginal likelihood under a multivariate Normal likelihood and a conjugate Normal-inverse Wishart prior.",
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        "marginalNIW,matrix,missing,missing,missing,missing-method",
        "marginalNIW,matrix,missing,missing,missing,vector-method",
        "marginalNIW,missing,ANY,matrix,numeric,missing-method",
        "marginalNIW,missing,list,list,numeric,missing-method",
        "marginalNIW-methods"
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      "page": "mixturebf-class",
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        "mixturebf",
        "mixturebf-class",
        "show,mixturebf-method"
      ]
    },
    {
      "page": "modelSelection",
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      "topics": [
        "modelsearchBlockDiag",
        "modelSelection",
        "modelSelection_eBayes"
      ]
    },
    {
      "page": "modelSelectionGGM",
      "title": "Bayesian variable selection for Gaussian graphical models",
      "topics": [
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        "modelSelectionGGM_eBayes"
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        "msfit_ggm-class",
        "msfit_ggm.coef",
        "show,msfit_ggm-method"
      ]
    },
    {
      "page": "msfit-class",
      "title": "Class \"msfit\"",
      "topics": [
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        "coefByModel,msfit-method",
        "coefByModel-methods",
        "msfit",
        "msfit-class",
        "msfit.coef",
        "msfit.plot",
        "msfit.predict",
        "show,msfit-method"
      ]
    },
    {
      "page": "msPriorSpec-class",
      "title": "Class \"msPriorSpec\"",
      "topics": [
        "aic",
        "bic",
        "bicprior",
        "emomprior",
        "exponentialprior",
        "groupemomprior",
        "groupimomprior",
        "groupmomprior",
        "groupzellnerprior",
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        "icarplusprior",
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        "imomprior",
        "modelbbprior",
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        "modelcomplexprior",
        "modelunifprior",
        "momprior",
        "msPriorSpec",
        "msPriorSpec-class",
        "normalidprior",
        "zellnerprior"
      ]
    },
    {
      "page": "plotprior",
      "title": "Plot estimated marginal prior inclusion probabilities",
      "topics": [
        "plotprior",
        "plotprior,cilfit-method",
        "plotprior-methods"
      ]
    },
    {
      "page": "postProb",
      "title": "Obtain posterior model probabilities",
      "topics": [
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        "postProb,cilfit-method",
        "postProb,localtest-method",
        "postProb,mixturebf-method",
        "postProb,msfit-method",
        "postProb,msfit_ggm-method",
        "postProb-methods"
      ]
    },
    {
      "page": "postSamples",
      "title": "Extract posterior samples from an object",
      "topics": [
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        "postSamples,mixturebf-method",
        "postSamples-methods"
      ]
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      "page": "mode2g",
      "title": "Moment and inverse moment prior elicitation",
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      ]
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      "page": "rnlp",
      "title": "Posterior sampling for regression parameters",
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        "rnlp,ANY,matrix,missing,missing,missing,character,character-method",
        "rnlp,ANY,matrix,missing,missing,missing,missing,missing-method",
        "rnlp,ANY,matrix,missing,missing,msfit,missing,missing-method",
        "rnlp,missing,missing,missing,missing,msfit,missing,missing-method",
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