Package: RoBSA 1.0.2
RoBSA: Robust Bayesian Survival Analysis
A framework for estimating ensembles of parametric survival models with different parametric families. The RoBSA framework uses Bayesian model-averaging to combine the competing parametric survival models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual predictors or preference for a parametric family (Bartoš, Aust & Haaf, 2022, <doi:10.1186/s12874-022-01676-9>). The user can define a wide range of informative priors for all parameters of interest. The package provides convenient functions for summary, visualizations, fit diagnostics, and prior distribution calibration.
Authors:
RoBSA_1.0.2.tar.gz
RoBSA_1.0.2.zip(r-4.5)RoBSA_1.0.2.zip(r-4.4)RoBSA_1.0.2.zip(r-4.3)
RoBSA_1.0.2.tgz(r-4.4-x86_64)RoBSA_1.0.2.tgz(r-4.4-arm64)RoBSA_1.0.2.tgz(r-4.3-x86_64)RoBSA_1.0.2.tgz(r-4.3-arm64)
RoBSA_1.0.2.tar.gz(r-4.5-noble)RoBSA_1.0.2.tar.gz(r-4.4-noble)
RoBSA.pdf |RoBSA.html✨
RoBSA/json (API)
NEWS
| # Install 'RoBSA' in R: |
| install.packages('RoBSA', repos = c('https://fbartos.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/fbartos/robsa/issues
bayesianmodel-averagingsurvival-analysis
Last updated 1 years agofrom:1342551a86. Checks:OK: 1 WARNING: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 02 2024 |
| R-4.5-win-x86_64 | WARNING | Nov 02 2024 |
| R-4.5-linux-x86_64 | WARNING | Nov 02 2024 |
| R-4.4-win-x86_64 | WARNING | Nov 02 2024 |
| R-4.4-mac-x86_64 | WARNING | Nov 02 2024 |
| R-4.4-mac-aarch64 | WARNING | Nov 02 2024 |
| R-4.3-win-x86_64 | WARNING | Nov 02 2024 |
| R-4.3-mac-x86_64 | WARNING | Nov 02 2024 |
| R-4.3-mac-aarch64 | WARNING | Nov 02 2024 |
Exports:calibrate_meta_analyticcalibrate_quartilescheck_RoBSAcheck_setupcontr.meandifcontr.orthonormaldiagnosticsdiagnostics_autocorrelationdiagnostics_densitydiagnostics_traceexp_aft_densityexp_aft_hazardexp_aft_log_densityexp_aft_log_hazardexp_aft_log_survivalexp_aft_meanexp_aft_pexp_aft_qexp_aft_rexp_aft_sdexp_aft_survivalextract_flexsurvgamma_aft_densitygamma_aft_hazardgamma_aft_log_densitygamma_aft_log_hazardgamma_aft_log_survivalgamma_aft_meangamma_aft_pgamma_aft_qgamma_aft_rgamma_aft_sdgamma_aft_survivalget_default_prior_auxget_default_prior_beta_altget_default_prior_beta_nullget_default_prior_factor_nullget_default_prior_interceptis.RoBSAllogis_aft_densityllogis_aft_hazardllogis_aft_log_densityllogis_aft_log_hazardllogis_aft_log_survivalllogis_aft_meanllogis_aft_pllogis_aft_qllogis_aft_rllogis_aft_sdllogis_aft_survivallnorm_aft_densitylnorm_aft_hazardlnorm_aft_log_densitylnorm_aft_log_hazardlnorm_aft_log_survivallnorm_aft_meanlnorm_aft_plnorm_aft_qlnorm_aft_rlnorm_aft_sdlnorm_aft_survivalplot_densityplot_hazardplot_modelsplot_predictionplot_survivalpriorprior_factorprior_informedprior_informed_medicine_namesprior_noneRoBSARoBSA.get_optionRoBSA.optionsset_autofit_controlset_convergence_checksweibull_aft_densityweibull_aft_hazardweibull_aft_log_densityweibull_aft_log_hazardweibull_aft_log_survivalweibull_aft_meanweibull_aft_pweibull_aft_qweibull_aft_rweibull_aft_sdweibull_aft_survival
Dependencies:BayesToolsbridgesamplingBrobdingnagclicodacolorspaceextraDistrfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigR6rbibutilsRColorBrewerRcppRdpackrjagsrlangrunjagsscalesstringistringrsurvivaltibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| RoBSA: Robust Bayesian survival analysis | RoBSA-package RoBSA.package RoBSA_package _PACKAGE |
| Create meta-analytic predictive prior distributions | calibrate_meta_analytic |
| Calibrate prior distributions based on quartiles | calibrate_quartiles |
| Check fitted RoBSA object for errors and warnings | check_RoBSA |
| Prints summary of '"RoBSA"' corresponding to the input | check_setup |
| Mean difference contrast matrix | contr.meandif |
| Default prior distributions | 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, |
| Visualizes MCMC diagnostics for a fitted RoBSA object | diagnostics diagnostics_autocorrelation diagnostics_density diagnostics_trace |
| Exponential AFT parametric family. | 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 |
| Extract parameter estimates from 'flexsurv' object | extract_flexsurv |
| Gamma AFT parametric family. | 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 |
| Reports whether x is a RoBSA object | is.RoBSA |
| Log-logistic AFT parametric family. | 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 |
| Log-normal AFT parametric family. | 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 |
| Models plot for a RoBSA object | plot_models |
| Survival plots for a RoBSA object | plot_density plot_hazard plot_prediction plot_survival |
| Plots a fitted RoBSA object | plot.RoBSA |
| Predict method for RoBSA objects. | predict.RoBSA |
| Prints a fitted RoBSA object | print.RoBSA |
| Prints summary object for RoBSA method | print.summary.RoBSA |
| Creates a prior distribution | prior |
| Creates a prior distribution for factors | prior_factor |
| Creates an informed prior distribution based on research | prior_informed |
| Names of medical subfields from the Cochrane database of systematic reviews | prior_informed_medicine_names |
| Creates a prior distribution | prior_none |
| Fit Robust Bayesian Survival Analysis | RoBSA |
| Control MCMC fitting process | RoBSA_control set_autofit_control set_autofit_control, set_convergence_checks |
| Options for the RoBSA package | RoBSA.get_option RoBSA.options RoBSA_options |
| Summarize fitted RoBSA object | summary.RoBSA |
| Updates a fitted RoBSA object | update.RoBSA |
| Weibull AFT parametric family. | 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 |
