approximateHierarchicalNormalPosterior
                        Approximate Bayesian posterior for hierarchical
                        Normal model
approximateLikelihood   Approximate a likelihood function
approximateSimplePosterior
                        Approximate simple Bayesian posterior
biasCorrectionInference
                        Bias Correction with Inference
buildLabelReferences    Build a list of references that map likelihood
                        names to integer labels for later use
computeBayesianMetaAnalysis
                        Compute a Bayesian random-effects meta-analysis
computeConfidenceInterval
                        Compute the point estimate and confidence
                        interval given a likelihood function
                        approximation
computeFixedEffectMetaAnalysis
                        Compute a fixed-effect meta-analysis
computeHierarchicalMetaAnalysis
                        Compute a Bayesian random-effects hierarchical
                        meta-analysis
constructDataModel      Construct 'DataModel' objects from approximate
                        likelihood or profile likelihood data
createApproximations    Create likelihood approximations from
                        individual-trajectory data
createSccsSimulationSettings
                        Create SCCS simulation settings
createSimulationSettings
                        Create simulation settings
customFunction          A custom function to approximate a log
                        likelihood function
detectApproximationType
                        Detect the type of likelihood approximation
                        based on the data format
extractSourceSpecificEffects
                        Compute source-specific biases and
                        bias-corrected estimates from hierarchical meta
                        analysis results
fitBiasDistribution     Fit Bias Distribution
generateBayesianHMAsettings
                        Generate settings for the Bayesian
                        random-effects hierarchical meta-analysis model
hermiteInterpolation    Cubic Hermite interpolation using both values
                        and gradients to approximate a log likelihood
                        function
hmaLikelihoodList       Example profile likelihoods for hierarchical
                        meta analysis with bias correction
likelihoodProfileLists
                        A bigger example of profile likelihoods for
                        hierarchical meta analysis with bias correction
loadCyclopsLibraryForJava
                        Load the Cyclops dynamic C++ library for use in
                        Java
ncLikelihoods           Example profile likelihoods for negative
                        control outcomes
ooiLikelihoods          Example profile likelihoods for a synthetic
                        outcome of interest
plotBiasCorrectionInference
                        Plot bias correction inference
plotBiasDistribution    Plot bias distributions
plotCovariateBalances   Plot covariate balances
plotEmpiricalNulls      Plot empirical null distributions
plotLikelihoodFit       Plot the likelihood approximation
plotMcmcTrace           Plot MCMC trace
plotMetaAnalysisForest
                        Create a forest plot
plotPerDbMcmcTrace      Plot MCMC trace for individual databases
plotPerDbPosterior      Plot posterior density per database
plotPosterior           Plot posterior density
plotPreparedPs          Plot the propensity score distribution
preparePsPlot           Prepare to plot the propensity score
                        distribution
prepareSccsIntervalData
                        Prepare SCCS interval data for pooled analysis
sequentialFitBiasDistribution
                        Fit Bias Distribution Sequentially or in Groups
simulateMetaAnalysisWithNegativeControls
                        Simulate survival data across a federated data
                        network, with negative control outcomes as
                        well.
simulatePopulations     Simulate survival data for multiple databases
skewNormal              The skew normal function to approximate a log
                        likelihood function
summarizeChain          Utility function to summarize MCMC samples
                        (posterior mean, median, HDI, std, etc.)
supportsJava8           Determine if Java virtual machine supports Java
