Package: RBesT 1.7-4
RBesT: R Bayesian Evidence Synthesis Tools
Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Weber et al. (2021) <doi:10.18637/jss.v100.i19> for details on applying this package while Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> explain details on the methodology.
Authors:
RBesT_1.7-4.tar.gz
RBesT_1.7-4.zip(r-4.5)RBesT_1.7-4.zip(r-4.4)RBesT_1.7-4.zip(r-4.3)
RBesT_1.7-4.tgz(r-4.4-x86_64)RBesT_1.7-4.tgz(r-4.4-arm64)RBesT_1.7-4.tgz(r-4.3-x86_64)RBesT_1.7-4.tgz(r-4.3-arm64)
RBesT_1.7-4.tar.gz(r-4.5-noble)RBesT_1.7-4.tar.gz(r-4.4-noble)
RBesT.pdf |RBesT.html✨
RBesT/json (API)
NEWS
# Install 'RBesT' in R: |
install.packages('RBesT', repos = c('https://novartis.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/novartis/rbest/issues
- AS - Ankylosing Spondylitis.
- colitis - Ulcerative Colitis.
- crohn - Crohn's disease.
- transplant - Transplant.
bayesianclinicalhistorical-datameta-analysis
Last updated 8 hours agofrom:bb349616ab. Checks:OK: 2 NOTE: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 21 2024 |
R-4.5-win-x86_64 | NOTE | Nov 21 2024 |
R-4.5-linux-x86_64 | OK | Nov 21 2024 |
R-4.4-win-x86_64 | NOTE | Nov 21 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 21 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 21 2024 |
R-4.3-win-x86_64 | NOTE | Nov 21 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 21 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 21 2024 |
Exports:automixfitBinaryExactCIdecision1Sdecision1S_boundarydecision2Sdecision2S_boundarydmixdmixdiffessforest_plotgMAPinv_logitlikelihoodlikelihood<-logitmixbetamixcombinemixfitmixgammamixmvnormmixnormmixstanvarmn2betamn2gammamn2normms2betams2gammaoc1Soc1Sdecisionoc2Soc2Sdecisionpmixpmixdiffpos1Spos2Spostmixpreddistqmixqmixdiffrmixrmixdiffrobustifysigmasigma<-
Dependencies:abindassertthatbackportsbayesplotBHcallrcheckmateclicolorspacedescdistributionaldplyrfansifarverFormulagenericsggplot2ggridgesgluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmenumDerivpillarpkgbuildpkgconfigplyrposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
R Bayesian Evidence Synthesis Tools | RBesT-package RBesT |
Ankylosing Spondylitis. | AS |
Automatic Fitting of Mixtures of Conjugate Distributions to a Sample | automixfit |
Exact Confidence interval for Binary Proportion | BinaryExactCI |
Ulcerative Colitis. | colitis |
Crohn's disease. | crohn |
Decision Function for 1 Sample Designs | decision1S oc1Sdecision |
Decision Boundary for 1 Sample Designs | decision1S_boundary decision1S_boundary.betaMix decision1S_boundary.gammaMix decision1S_boundary.normMix |
Decision Function for 2 Sample Designs | decision2S oc2Sdecision |
Decision Boundary for 2 Sample Designs | decision2S_boundary decision2S_boundary.betaMix decision2S_boundary.gammaMix decision2S_boundary.normMix |
Effective Sample Size for a Conjugate Prior | ess ess.betaMix ess.gammaMix ess.normMix |
Forest Plot | forest_plot |
Meta-Analytic-Predictive Analysis for Generalized Linear Models | as.matrix.gMAP coef.gMAP fitted.gMAP gMAP print.gMAP summary.gMAP |
Read and Set Likelihood to the Corresponding Conjugate Prior | likelihood likelihood<- |
Logit (log-odds) and inverse-logit function. | inv_logit lodds logit |
Mixture Distributions | dmix mix pmix qmix rmix [[.mix |
Beta Mixture Density | mixbeta mn2beta ms2beta print.betaBinomialMix print.betaMix summary.betaBinomialMix summary.betaMix |
Combine Mixture Distributions | mixcombine |
Difference of mixture distributions | dmixdiff mixdiff pmixdiff qmixdiff rmixdiff |
Fit of Mixture Densities to Samples | mixfit mixfit.array mixfit.default mixfit.gMAP mixfit.gMAPpred |
The Gamma Mixture Distribution | mixgamma mn2gamma ms2gamma print.gammaExpMix print.gammaMix print.gammaPoissonMix summary.gammaMix summary.gammaPoissonMix |
Multivariate Normal Mixture Density | mixmvnorm print.mvnormMix sigma.mvnormMix summary.mvnormMix |
Normal Mixture Density | mixnorm mn2norm print.normMix sigma sigma.normMix sigma<- summary.normMix |
Plot mixture distributions | mixplot plot.mix plot.mvnormMix |
Mixture distributions as 'brms' priors | mixstanvar |
Operating Characteristics for 1 Sample Design | oc1S oc1S.betaMix oc1S.gammaMix oc1S.normMix |
Operating Characteristics for 2 Sample Design | oc2S oc2S.betaMix oc2S.gammaMix oc2S.normMix |
Diagnostic plots for EM fits | plot.EM |
Diagnostic plots for gMAP analyses | plot.gMAP |
Probability of Success for a 1 Sample Design | pos1S pos1S.betaMix pos1S.gammaMix pos1S.normMix |
Probability of Success for 2 Sample Design | pos2S pos2S.betaMix pos2S.gammaMix pos2S.normMix |
Conjugate Posterior Analysis | postmix postmix.betaMix postmix.gammaMix postmix.normMix |
Predictive Distributions for Mixture Distributions | preddist preddist.betaMix preddist.gammaMix preddist.mvnormMix preddist.normMix |
Predictions from gMAP analyses | as.matrix.gMAPpred predict.gMAP print.gMAPpred summary.gMAPpred |
Robustify Mixture Priors | robustify robustify.betaMix robustify.gammaMix robustify.normMix |
Transplant. | transplant |