Create object to adapt proposal scale to coerce average acceptance rate.

Usage

scale_adapter(
  algorithm = "dual_averaging",
  initial_scale = NULL,
  target_accept_prob = NULL,
  ...
)

Arguments

algorithm

String specifying algorithm to use. One of:

"stochastic_approximation" to use a Robbins-Monro (1951) based scheme,
"dual_averaging" to use dual-averaging scheme of Nesterov (2009).

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.

...

Any additional algorithmic parameters to pass through to dual_averaging_scale_adapter() or stochastic_approximation_scale_adapter().

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 be NULL if unused).
state a zero-argument function for accessing current values of adapter state variables.

References

Nesterov, Y. (2009). Primal-dual subgradient methods for convex problems. Mathematical Programming, 120(1), 221-259.

Robbins, H., & Monro, S. (1951). A stochastic approximation method. The Annals of Mathematical Statistics, 400-407.

Examples

proposal <- barker_proposal()
adapter <- scale_adapter(initial_scale = 1., target_accept_prob = 0.4)
adapter$initialize(proposal, chain_state(c(0, 0)))