Bayesian Regression for Combinatorial Response Data

Documentation for package ‘combreg’ version 0.2.0

as.mcmc.crr_fit	Convert to coda mcmc.list
as_draws.crr_fit	Convert to posterior draws_array
coef.crr_fit	Posterior mean coefficients
coef_precompute	Precompute quantities for the conjugate coefficient update
crr	Bayesian combinatorial response regression
crr_benchmark	Benchmark samplers on a common data set
crr_constraints	Constraint system for combinatorial responses
crr_control	Sampler control parameters
crr_diagnostics	MCMC and regression diagnostics report
crr_ess	Effective sample sizes
crr_ppc	Posterior predictive goodness-of-fit checks
crr_prior	Prior specification for crr models
crr_rhat	Split-Rhat convergence diagnostics
draw_utility	Draw latent utilities from their truncated-normal full conditional
dual_feasible	Check dual-certificate feasibility
fitted.crr_fit	Fitted responses
init_dual	Initialize dual certificates
is_feasible	Check feasibility of responses
is_tum	Check total unimodularity
plot.crr_fit	Diagnostic plots for a crr fit
predict.crr_fit	Posterior predictions
random_constraints	Generate a random totally unimodular constraint system
residuals.crr_fit	Response residuals
sample_dual	Update dual certificates given latent utilities
sample_utility	Metropolis-Hastings update of the latent utilities
simulate_crr	Simulate combinatorial response regression data
summary.crr_fit	Posterior summary of a crr fit
update_coef	Conjugate Gaussian update of the regression coefficients