stochastic_approximation_scale_adapter {rmcmc} | R Documentation |
Create object to adapt proposal scale to coerce average acceptance rate using a Robbins and Monro (1951) scheme.
Description
When combined with covariance_shape_adapter()
corresponds to Algorithm 4 in
Andrieu and Thoms (2009).
Usage
stochastic_approximation_scale_adapter(
initial_scale = NULL,
target_accept_prob = NULL,
kappa = 0.6
)
Arguments
initial_scale |
Initial value to use for scale parameter. If not set explicitly a proposal and dimension dependent default will be used. |
target_accept_prob |
Target value for average accept probability for chain. If not set a proposal dependent default will be used. |
kappa |
Decay rate exponent in |
Value
List of functions with entries
-
initialize
, a function for initializing adapter state and proposal parameters at beginning of chain, -
update
a function for updating adapter state and proposal parameters on each chain iteration, -
finalize
a function for performing any final updates to adapter state and proposal parameters on completion of chain sampling (may beNULL
if unused). -
state
a zero-argument function for accessing current values of adapter state variables.
References
Andrieu, C., & Thoms, J. (2008). A tutorial on adaptive MCMC. Statistics and Computing, 18, 343-373.
Robbins, H., & Monro, S. (1951). A stochastic approximation method. The Annals of Mathematical Statistics, 400-407.
Examples
proposal <- barker_proposal()
adapter <- stochastic_approximation_scale_adapter(
initial_scale = 1., target_accept_prob = 0.4
)
adapter$initialize(proposal, chain_state(c(0, 0)))