Package index • rankclust

Density and Random Data Generation functions Functions that allow for calculating the density of ordinal comparison data and random sampling of BTL and Rank-Clustered BTL data.
`dBTL()`	Calculate the density of ordinal comparison data based on BTL models
`rBTL()`	Random data generation from standard BTL models
`rRCBTL()`	Random data generation from Rank-Clustered BTL models
`posterior_density()`	Calculate proportional posterior density for mcmc samples in a Rank-Clustered BTL model.
Model Estimation Functions Functions that allow for estimation of Bayesian BTL or Rank-Clustered BTL models.
`mcmc_BTL()`	Fit Bayesian BTL model to ordinal comparison data using multiple MCMC chains
`mcmc_RCBTL()`	Fit Bayesian Rank-Clustered BTL model to ordinal comparison data using multiple MCMC chains
Model Assessment and Results Visualization Function Functions to visualize convergence/mixing of MCMC chains and parameter posteriors.
`trace_ggplots()`	Trace ggplots for (Rank-Clustered) BTL models.
`posterior_ggplots()`	Posterior ggplots for worth parameters in (Rank-Clustered) BTL models.
`cluster_ggplots()`	Rank-Cluster ggplots for Rank-Clustered BTL models.
Helper Functions Functions used during model-fitting that are not needed by the user, but are provided for completeness and reproducibility.
`fit_BTL()`	Fit a Bayesian BTL model to ordinal comparison data (recommended for internal use only; use mcmc_BTL function instead)
`fit_RCBTL()`	Fit a Bayesian Rank-Clustered BTL model to ordinal comparison data (recommended for internal use only; use mcmc_RCBTL function instead)
`obtain_constants()`	Calculation of constants for Gibbs sampling of worth parameters via data augmentation (internal use only)
`sample_nu()`	Sampling of unique parameter worth values, nu, in Bayesian Rank-Clustered BTL models (internal use only)
`sample_partition()`	Partition sampling in Bayesian Rank-Clustered BTL models (internal use only)