Hierarchical Piecewise Regression with Smoothed Change-Points

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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