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:František Bartoš [aut, cre], Julia M. Haaf [ths], Matthew Denwood [cph], Martyn Plummer [cph]

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)
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Peer review:

Bug tracker:https://github.com/fbartos/robsa/issues

On CRAN:

bayesianmodel-averagingsurvival-analysis

87 exports 8 stars 1.33 score 42 dependencies 1 scripts 188 downloads

Last updated 1 years agofrom:1342551a86. Checks:OK: 1 WARNING: 8. Indexed: yes.

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