| append_chains | Append MCMC chains (objects of class coda::mcmc) |
| append_chains.default | Append MCMC chains (objects of class coda::mcmc) |
| append_chains.mcmc | Append MCMC chains (objects of class coda::mcmc) |
| append_chains.mcmc.list | Append MCMC chains (objects of class coda::mcmc) |
| automatic-stop | Convergence Monitoring |
| check_initial | Checks the initial values of the MCMC |
| convergence-checker | Convergence Monitoring |
| convergence_auto | Convergence Monitoring |
| convergence_gelman | Convergence Monitoring |
| convergence_geweke | Convergence Monitoring |
| convergence_heildel | Convergence Monitoring |
| cov_recursive | Recursive algorithms for computing variance and mean |
| fmcmc | A friendly MCMC framework |
| fmcmc_kernel | Transition Kernels for MCMC |
| kernels | Transition Kernels for MCMC |
| kernel_adapt | Adaptive Metropolis (AM) Transition Kernel |
| kernel_am | Adaptive Metropolis (AM) Transition Kernel |
| kernel_mirror | Mirror Transition Kernels |
| kernel_new | Transition Kernels for MCMC |
| kernel_nmirror | Mirror Transition Kernels |
| kernel_normal | Gaussian Transition Kernel |
| kernel_normal_reflective | Gaussian Transition Kernel |
| kernel_ram | Robust Adaptive Metropolis (RAM) Transition Kernel |
| kernel_umirror | Mirror Transition Kernels |
| kernel_unif | Uniform Transition Kernel |
| kernel_unif_reflective | Uniform Transition Kernel |
| MCMC | Markov Chain Monte Carlo |
| MCMC.default | Markov Chain Monte Carlo |
| MCMC.mcmc | Markov Chain Monte Carlo |
| MCMC.mcmc.list | Markov Chain Monte Carlo |
| mean_recursive | Recursive algorithms for computing variance and mean |
| Metropolis-Hastings | Markov Chain Monte Carlo |
| new_progress_bar | Progress bar |
| plan_update_sequence | Parameters' update sequence |
| reflect_on_boundaries | Reflective Boundaries |