Robust Markov Chain Monte Carlo Methods

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Documentation for package ‘rmcmc’ version 0.1.1

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

Help Pages

barker_proposal	Create a new Barker proposal object.
bimodal_barker_proposal	Create a new Barker proposal object with bimodal noise distribution.
chain_state	Construct a new chain state.
covariance_shape_adapter	Create object to adapt proposal with shape based on estimate of target distribution covariance matrix.
dual_averaging_scale_adapter	Create object to adapt proposal scale to coerce average acceptance rate using dual averaging scheme of Nesterov (2009) and Hoffman and Gelman (2014).
example_gaussian_stan_model	Construct an example BridgeStan 'StanModel' object for a Gaussian model.
hamiltonian_proposal	Create a new Hamiltonian proposal object.
langevin_proposal	Create a new Langevin proposal object.
random_walk_proposal	Create a new (Gaussian) random walk proposal object.
robust_shape_adapter	Create object to adapt proposal shape (and scale) using robust adaptive Metropolis algorithm of Vihola (2012).
sample_chain	Sample a Markov chain
scale_adapter	Create object to adapt proposal scale to coerce average acceptance rate.
shape_adapter	Create object to adapt proposal shape.
stochastic_approximation_scale_adapter	Create object to adapt proposal scale to coerce average acceptance rate using a Robbins and Monro (1951) scheme.
target_distribution_from_log_density_formula	Construct target distribution from a formula specifying log density.
target_distribution_from_stan_model	Construct target distribution from a BridgeStan 'StanModel' object.
variance_shape_adapter	Create object to adapt proposal with per dimension scales based on estimates of target distribution variances.