{
  "_id": "6a23f33fa1338011a79ede5b",
  "Package": "RoBSA",
  "Type": "Package",
  "Title": "Robust Bayesian Survival Analysis",
  "Version": "1.0.4",
  "Maintainer": "František Bartoš <f.bartos96@gmail.com>",
  "Authors@R": "c( \nperson(\"František\", \"Bartoš\", role = c(\"aut\", \"cre\"),\nemail = \"f.bartos96@gmail.com\", comment = c(ORCID = \"0000-0002-0018-5573\")),\nperson(\"Julia M.\", \"Haaf\", role = \"ths\",\ncomment = c(ORCID = \"0000-0001-5122-706X\")),\nperson(\"Matthew\", \"Denwood\", role=\"cph\",\ncomment=\"Original copyright holder of some modified code where indicated.\"),\nperson(\"Martyn\", \"Plummer\", role=\"cph\",\ncomment=\"Original copyright holder of some modified code where indicated.\")\n)",
  "Description": "A framework for estimating ensembles of parametric\nsurvival models with different parametric families. The RoBSA\nframework uses Bayesian model-averaging to combine the\ncompeting parametric survival models into a model ensemble,\nweights the posterior parameter distributions based on\nposterior model probabilities and uses Bayes factors to test\nfor the presence or absence of the individual predictors or\npreference for a parametric family (Bartoš, Aust & Haaf, 2022,\n<doi:10.1186/s12874-022-01676-9>). The user can define a wide\nrange of informative priors for all parameters of interest. The\npackage provides convenient functions for summary,\nvisualizations, fit diagnostics, and prior distribution\ncalibration.",
  "URL": "https://fbartos.github.io/RoBSA/",
  "BugReports": "https://github.com/FBartos/RoBSA/issues",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "RoxygenNote": "7.2.3",
  "SystemRequirements": "JAGS >= 4.3.1 (https://mcmc-jags.sourceforge.io/)",
  "RdMacros": "Rdpack",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-06 10:11:35 UTC",
    "User": "root"
  },
  "Author": "František Bartoš [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-0018-5573>), Julia M. Haaf [ths]\n(ORCID: <https://orcid.org/0000-0001-5122-706X>), Matthew\nDenwood [cph] (Original copyright holder of some modified code\nwhere indicated.), Martyn Plummer [cph] (Original copyright\nholder of some modified code where indicated.)",
  "Config/pak/sysreqs": "jags",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-05-07 15:08:03 UTC",
  "RemoteUrl": "https://github.com/cran/RoBSA",
  "RemoteRef": "HEAD",
  "RemoteSha": "9d300978c9a717aa1ff715b92ddb36f75ab0aa79",
  "MD5sum": "bc9d22ddbe45e21392899632af62d53f",
  "_user": "cran",
  "_type": "src",
  "_file": "RoBSA_1.0.4.tar.gz",
  "_fileid": "2309cd0fc50b62c071cbbcc4a6fdc0aef44b4952c1ef181f7db9c59c8a786a87",
  "_filesize": 354450,
  "_sha256": "2309cd0fc50b62c071cbbcc4a6fdc0aef44b4952c1ef181f7db9c59c8a786a87",
  "_created": "2026-06-06T10:11:35.000Z",
  "_published": "2026-06-06T10:15:27.279Z",
  "_distro": "noble",
  "_jobs": [
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  "_buildurl": "https://github.com/r-universe/cran/actions/runs/27059441602",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/RoBSA",
  "_commit": {
    "id": "9d300978c9a717aa1ff715b92ddb36f75ab0aa79",
    "author": "František Bartoš <f.bartos96@gmail.com>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 1.0.4\n",
    "time": 1778166483
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  "_maintainer": {
    "name": "František Bartoš",
    "email": "f.bartos96@gmail.com",
    "login": "fbartos",
    "bluesky": "@fbartos.bsky.social",
    "orcid": "0000-0002-0018-5573",
    "twitter": "@BartosFra",
    "description": "A PostDoc at the University of Amsterdam. I’m interested in meta-analyses, publication bias, replicability, and Bayesian inference.",
    "uuid": 38475991
  },
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  "_dependencies": [
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      "package": "R",
      "version": ">= 4.0.0",
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    {
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  "_owner": "cran",
  "_selfowned": false,
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  "_updates": [
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      "week": "2026-19",
      "n": 1
    }
  ],
  "_tags": [
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      "name": "1.0.4",
      "date": "2026-05-07"
    }
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/RoBSA"
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  "_devurl": "https://github.com/fbartos/robsa",
  "_pkgdown": "https://fbartos.github.io/RoBSA/",
  "_searchresults": 4,
  "_topics": [
    "jags",
    "cpp"
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  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
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    "extra/contents.json",
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    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "extra/RoBSA.html",
    "manual.pdf"
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  "_homeurl": "https://github.com/fbartos/robsa",
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  "_releases": [
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      "date": "2022-05-27"
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      "date": "2025-03-24"
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      "version": "1.0.4",
      "date": "2026-05-07"
    }
  ],
  "_exports": [
    "calibrate_meta_analytic",
    "calibrate_quartiles",
    "check_RoBSA",
    "check_setup",
    "contr.independent",
    "contr.meandif",
    "contr.orthonormal",
    "diagnostics",
    "diagnostics_autocorrelation",
    "diagnostics_density",
    "diagnostics_trace",
    "exp_aft_density",
    "exp_aft_hazard",
    "exp_aft_log_density",
    "exp_aft_log_hazard",
    "exp_aft_log_survival",
    "exp_aft_mean",
    "exp_aft_p",
    "exp_aft_q",
    "exp_aft_r",
    "exp_aft_sd",
    "exp_aft_survival",
    "extract_flexsurv",
    "gamma_aft_density",
    "gamma_aft_hazard",
    "gamma_aft_log_density",
    "gamma_aft_log_hazard",
    "gamma_aft_log_survival",
    "gamma_aft_mean",
    "gamma_aft_p",
    "gamma_aft_q",
    "gamma_aft_r",
    "gamma_aft_sd",
    "gamma_aft_survival",
    "get_default_prior_aux",
    "get_default_prior_beta_alt",
    "get_default_prior_beta_null",
    "get_default_prior_factor_null",
    "get_default_prior_intercept",
    "is.RoBSA",
    "llogis_aft_density",
    "llogis_aft_hazard",
    "llogis_aft_log_density",
    "llogis_aft_log_hazard",
    "llogis_aft_log_survival",
    "llogis_aft_mean",
    "llogis_aft_p",
    "llogis_aft_q",
    "llogis_aft_r",
    "llogis_aft_sd",
    "llogis_aft_survival",
    "lnorm_aft_density",
    "lnorm_aft_hazard",
    "lnorm_aft_log_density",
    "lnorm_aft_log_hazard",
    "lnorm_aft_log_survival",
    "lnorm_aft_mean",
    "lnorm_aft_p",
    "lnorm_aft_q",
    "lnorm_aft_r",
    "lnorm_aft_sd",
    "lnorm_aft_survival",
    "plot_density",
    "plot_hazard",
    "plot_models",
    "plot_prediction",
    "plot_survival",
    "prior",
    "prior_factor",
    "prior_informed",
    "prior_informed_medicine_names",
    "prior_none",
    "RoBSA",
    "RoBSA.get_option",
    "RoBSA.options",
    "set_autofit_control",
    "set_convergence_checks",
    "weibull_aft_density",
    "weibull_aft_hazard",
    "weibull_aft_log_density",
    "weibull_aft_log_hazard",
    "weibull_aft_log_survival",
    "weibull_aft_mean",
    "weibull_aft_p",
    "weibull_aft_q",
    "weibull_aft_r",
    "weibull_aft_sd",
    "weibull_aft_survival"
  ],
  "_help": [
    {
      "page": "RoBSA-package",
      "title": "RoBSA: Robust Bayesian survival analysis",
      "topics": [
        "RoBSA-package",
        "RoBSA.package",
        "RoBSA_package",
        "_PACKAGE"
      ]
    },
    {
      "page": "calibrate_meta_analytic",
      "title": "Create meta-analytic predictive prior distributions",
      "topics": [
        "calibrate_meta_analytic"
      ]
    },
    {
      "page": "calibrate_quartiles",
      "title": "Calibrate prior distributions based on quartiles",
      "topics": [
        "calibrate_quartiles"
      ]
    },
    {
      "page": "check_RoBSA",
      "title": "Check fitted RoBSA object for errors and warnings",
      "topics": [
        "check_RoBSA"
      ]
    },
    {
      "page": "check_setup",
      "title": "Prints summary of '\"RoBSA\"' corresponding to the input",
      "topics": [
        "check_setup"
      ]
    },
    {
      "page": "contr.BayesTools",
      "title": "BayesTools Contrast Matrices",
      "topics": [
        "contr.BayesTools",
        "contr.independent",
        "contr.meandif",
        "contr.orthonormal"
      ]
    },
    {
      "page": "default_prior",
      "title": "Default prior distributions",
      "topics": [
        "default_prior",
        "get_default_prior_aux",
        "get_default_prior_beta_alt",
        "get_default_prior_beta_alt,",
        "get_default_prior_beta_null",
        "get_default_prior_beta_null,",
        "get_default_prior_factor_alt",
        "get_default_prior_factor_alt,",
        "get_default_prior_factor_null",
        "get_default_prior_factor_null,",
        "get_default_prior_intercept",
        "get_default_prior_intercept,"
      ]
    },
    {
      "page": "diagnostics",
      "title": "Visualizes MCMC diagnostics for a fitted RoBSA object",
      "topics": [
        "diagnostics",
        "diagnostics_autocorrelation",
        "diagnostics_density",
        "diagnostics_trace"
      ]
    },
    {
      "page": "exp-aft",
      "title": "Exponential AFT parametric family.",
      "topics": [
        "exp-aft",
        "exp_aft_density",
        "exp_aft_hazard",
        "exp_aft_log_density",
        "exp_aft_log_hazard",
        "exp_aft_log_survival",
        "exp_aft_mean",
        "exp_aft_p",
        "exp_aft_q",
        "exp_aft_r",
        "exp_aft_sd",
        "exp_aft_survival"
      ]
    },
    {
      "page": "extract_flexsurv",
      "title": "Extract parameter estimates from 'flexsurv' object",
      "topics": [
        "extract_flexsurv"
      ]
    },
    {
      "page": "gamma-aft",
      "title": "Gamma AFT parametric family.",
      "topics": [
        "gamma-aft",
        "gamma_aft_density",
        "gamma_aft_hazard",
        "gamma_aft_log_density",
        "gamma_aft_log_hazard",
        "gamma_aft_log_survival",
        "gamma_aft_mean",
        "gamma_aft_p",
        "gamma_aft_q",
        "gamma_aft_r",
        "gamma_aft_sd",
        "gamma_aft_survival"
      ]
    },
    {
      "page": "is.RoBSA",
      "title": "Reports whether x is a RoBSA object",
      "topics": [
        "is.RoBSA"
      ]
    },
    {
      "page": "llogis-aft",
      "title": "Log-logistic AFT parametric family.",
      "topics": [
        "llogis-aft",
        "llogis_aft_density",
        "llogis_aft_hazard",
        "llogis_aft_log_density",
        "llogis_aft_log_hazard",
        "llogis_aft_log_survival",
        "llogis_aft_mean",
        "llogis_aft_p",
        "llogis_aft_q",
        "llogis_aft_r",
        "llogis_aft_sd",
        "llogis_aft_survival"
      ]
    },
    {
      "page": "lnorm-aft",
      "title": "Log-normal AFT parametric family.",
      "topics": [
        "lnorm-aft",
        "lnorm_aft_density",
        "lnorm_aft_hazard",
        "lnorm_aft_log_density",
        "lnorm_aft_log_hazard",
        "lnorm_aft_log_survival",
        "lnorm_aft_mean",
        "lnorm_aft_p",
        "lnorm_aft_q",
        "lnorm_aft_r",
        "lnorm_aft_sd",
        "lnorm_aft_survival"
      ]
    },
    {
      "page": "plot_models",
      "title": "Models plot for a RoBSA object",
      "topics": [
        "plot_models"
      ]
    },
    {
      "page": "plot_prediction",
      "title": "Survival plots for a RoBSA object",
      "topics": [
        "plot_density",
        "plot_hazard",
        "plot_prediction",
        "plot_survival"
      ]
    },
    {
      "page": "plot.RoBSA",
      "title": "Plots a fitted RoBSA object",
      "topics": [
        "plot.RoBSA"
      ]
    },
    {
      "page": "predict.RoBSA",
      "title": "Predict method for RoBSA objects.",
      "topics": [
        "predict.RoBSA"
      ]
    },
    {
      "page": "print.RoBSA",
      "title": "Prints a fitted RoBSA object",
      "topics": [
        "print.RoBSA"
      ]
    },
    {
      "page": "print.summary.RoBSA",
      "title": "Prints summary object for RoBSA method",
      "topics": [
        "print.summary.RoBSA"
      ]
    },
    {
      "page": "prior",
      "title": "Creates a prior distribution",
      "topics": [
        "prior"
      ]
    },
    {
      "page": "prior_factor",
      "title": "Creates a prior distribution for factors",
      "topics": [
        "prior_factor"
      ]
    },
    {
      "page": "prior_informed",
      "title": "Creates an informed prior distribution based on research",
      "topics": [
        "prior_informed"
      ]
    },
    {
      "page": "prior_informed_medicine_names",
      "title": "Names of medical subfields from the Cochrane database of systematic reviews",
      "topics": [
        "prior_informed_medicine_names"
      ]
    },
    {
      "page": "prior_none",
      "title": "Creates a prior distribution",
      "topics": [
        "prior_none"
      ]
    },
    {
      "page": "RoBSA",
      "title": "Fit Robust Bayesian Survival Analysis",
      "topics": [
        "RoBSA"
      ]
    },
    {
      "page": "RoBSA_control",
      "title": "Control MCMC fitting process",
      "topics": [
        "RoBSA_control",
        "set_autofit_control",
        "set_autofit_control,",
        "set_convergence_checks"
      ]
    },
    {
      "page": "RoBSA_options",
      "title": "Options for the RoBSA package",
      "topics": [
        "RoBSA.get_option",
        "RoBSA.options",
        "RoBSA_options"
      ]
    },
    {
      "page": "summary.RoBSA",
      "title": "Summarize fitted RoBSA object",
      "topics": [
        "summary.RoBSA"
      ]
    },
    {
      "page": "update.RoBSA",
      "title": "Updates a fitted RoBSA object",
      "topics": [
        "update.RoBSA"
      ]
    },
    {
      "page": "weibull-aft",
      "title": "Weibull AFT parametric family.",
      "topics": [
        "weibull-aft",
        "weibull_aft_density",
        "weibull_aft_hazard",
        "weibull_aft_log_density",
        "weibull_aft_log_hazard",
        "weibull_aft_log_survival",
        "weibull_aft_mean",
        "weibull_aft_p",
        "weibull_aft_q",
        "weibull_aft_r",
        "weibull_aft_sd",
        "weibull_aft_survival"
      ]
    }
  ],
  "_readme": "https://github.com/cran/RoBSA/raw/HEAD/README.md",
  "_rundeps": [
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    "bridgesampling",
    "Brobdingnag",
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    "cpp11",
    "extraDistr",
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    "ggplot2",
    "glue",
    "gtable",
    "isoband",
    "labeling",
    "lattice",
    "lifecycle",
    "magrittr",
    "Matrix",
    "mvtnorm",
    "R6",
    "rbibutils",
    "RColorBrewer",
    "Rcpp",
    "RcppArmadillo",
    "Rdpack",
    "rjags",
    "rlang",
    "runjags",
    "S7",
    "scales",
    "stringi",
    "stringr",
    "survival",
    "vctrs",
    "viridisLite",
    "withr"
  ],
  "_sysdeps": [
    {
      "shlib": "libjags",
      "package": "jags",
      "headers": "jags",
      "source": "jags",
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      "homepage": "https://mcmc-jags.sourceforge.io",
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    },
    {
      "shlib": "libjrmath",
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      "headers": "jags",
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    },
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      "shlib": "libstdc++",
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      "homepage": "https://mcmc-jags.sourceforge.io",
      "description": "Just Another Gibbs Sampler for Bayesian MCMC - binary\nJAGS is Just Another Gibbs Sampler.  It is a program for analysis of\nBayesian hierarchical models using Markov Chain Monte Carlo (MCMC)\nsimulation not wholly unlike BUGS.\n\nJAGS was written with three aims in mind:\n* To have an engine for the BUGS language that runs on Unix\n* To be extensible, allowing users to write their own functions,\ndistributions and samplers.\n* To be a plaftorm for experimentation with ideas in Bayesian modelling\n\nThis package contains the 'jags' binary as well as the associated\nshared library modules loaded by the binary."
    },
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
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      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
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  "_nocasepkg": "robsa",
  "_universes": [
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  "_indexurl": "https://fbartos.r-universe.dev/RoBSA",
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}