# Hierarchical Piecewise Regression with Smoothed Change-Points

## Documentation for package ‘smoothbp’ version 0.2.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

as.data.frame.smoothbp_fit | Convert draws to a data frame
bayes_factor.smoothbp_fit | Bayes Factor for smoothbp_fit
bridge_sampler.smoothbp_fit | Bridge Sampler for smoothbp_fit
fitted.smoothbp_fit | Fitted values for smoothbp_fit objects
fixed | Fix a parameter at a specific value
hypothesis | Test hypotheses and compute evidence ratios from posterior draws
log_lik | Pointwise log-likelihood matrix
log_lik.smoothbp_fit | Pointwise log-likelihood matrix
pip | Posterior inclusion probabilities from a spike-and-slab fit
plot.smoothbp_fit | Trace and density plots for a smoothbp_fit
plot.smoothbp_pip | Plot posterior inclusion probabilities
print.smoothbp_fit | Print a smoothbp_fit
prior_gamma | Specify a gamma prior for a parameter
prior_invgamma | Specify an inverse-gamma prior for a variance component
prior_normal | Specify a normal (or truncated normal) prior for a regression coefficient
prior_spike_slab | Specify a spike-and-slab prior for variable selection
recovery_plot | Parameter recovery plot
robustify | Robustify a smoothbp_fit object using a Bayesian Sandwich approach
simulate_smoothbp | Simulate data from the smooth change-point model
smoothbp | Fit a hierarchical piecewise regression model with smoothed change-points
smoothbp_priors | Collect priors for all model parameters
smoothbp_ss | Fit a smooth change-point model with spike-and-slab variable selection
space_omega_priors | Generate evenly spaced priors for candidate breakpoints
summary.smoothbp_fit | Summarise a smoothbp_fit
summary.smoothbp_ss_fit | Summarise a smoothbp_ss_fit
tab_smoothbp | Fixed-effects table for smoothbp_fit objects
trace_plot | Trace plots with automatic poor-mixing highlighting
true_params | Print true parameters from a simulated dataset
update.smoothbp_fit | Update a fitted smoothbp model