TNM                     Triglycerides Network Meta (TNM) data
bayes.nmr               Fit Bayesian Network Meta-Regression
                        Hierarchical Models Using Heavy-Tailed
                        Multivariate Random Effects with
                        Covariate-Dependent Variances
bayes.parobs            Fit Bayesian Inference for Multivariate
                        Meta-Regression With a Partially Observed
                        Within-Study Sample Covariance Matrix
cholesterol             26 double-blind, randomized, active, or
                        placebo-controlled clinical trials on patients
                        with primary hypercholesterolemia sponsored by
                        Merck & Co., Inc., Kenilworth, NJ, USA.
fitted.bayes.parobs     get fitted values
fitted.bayesnmr         get fitted values
hpd                     get the highest posterior density (HPD)
                        interval
hpd.bayes.parobs        get the highest posterior density (HPD)
                        interval or equal-tailed credible interval
hpd.bayesnmr            get the highest posterior density (HPD)
                        interval
metapack                metapack: a package for Bayesian meta-analysis
                        and network meta-analysis
model.comp              compute the model comparison measures: DIC,
                        LPML, or Pearson's residuals
model.comp.bayes.parobs
                        compute the model comparison measures
model.comp.bayesnmr     get compute the model comparison measures
plot.bayes.parobs       get goodness of fit
plot.bayesnmr           get goodness of fit
plot.sucra              plot the surface under the cumulative ranking
                        curve (SUCRA)
print.bayes.parobs      Print results
print.bayesnmr          Print results
sucra                   get surface under the cumulative ranking curve
                        (SUCRA)
sucra.bayesnmr          get surface under the cumulative ranking curve
                        (SUCRA)
summary.bayes.parobs    'summary' method for class "'bayes.parobs'"
summary.bayesnmr        Summarize results
