A friendly MCMC framework


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Documentation for package ‘fmcmc’ version 0.3-0

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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