| bsreg-package | Bayesian Spatial Regression Models |
| as.mcmc.bm | Methods for 'coda' Markov chain Monte Carlo objects |
| blm | Fit a Bayesian model |
| bm | Fit a Bayesian model |
| bm.bm | Fit a Bayesian model |
| bm.formula | Fit a Bayesian model |
| bsar | Fit a Bayesian model |
| bsdem | Fit a Bayesian model |
| bsdm | Fit a Bayesian model |
| bsem | Fit a Bayesian model |
| bslx | Fit a Bayesian model |
| bsv | Fit a Bayesian model |
| burn | Burn-in and tune a Bayesian model sampler |
| cigarettes | Cigarette demand |
| coda | Methods for 'coda' Markov chain Monte Carlo objects |
| sample | Obtain draws from a Bayesian model sampler |
| set_HS | Set up a Normal-Gamma prior |
| set_mh | Settings to tune a Metropolis-Hastings step |
| set_NG | Set up a Normal-Gamma prior |
| set_options | Set up Bayesian model priors and settings |
| set_SAR | Set up a spatial prior |
| set_SEM | Set up a spatial prior |
| set_SLX | Set up a spatial prior |
| set_SNG | Set up a Normal-Gamma prior |
| set_SV | Set up a volatility prior |
| tune | Burn-in and tune a Bayesian model sampler |
| us_states | United States Historical States |