Create object to adapt proposal scale to coerce average acceptance rate using dual averaging scheme of Nesterov (2009) and Hoffman and Gelman (2014).

Usage

dual_averaging_scale_adapter(
  initial_scale = NULL,
  target_accept_prob = NULL,
  kappa = 0.75,
  gamma = 0.05,
  iteration_offset = 10,
  mu = NULL
)

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 [0.5, 1] for adaptation learning rate.
gamma: Regularization coefficient for (log) scale in dual averaging algorithm. Controls amount of regularization of (log) scale towards mu. Should be set to a non-negative value. Defaults to value recommended in Hoffman and Gelman (2014).
iteration_offset: Offset to chain iteration used for the iteration based weighting of the adaptation statistic error estimate. Should be set to a non-negative value. A value greater than zero has the effect of stabilizing early iterations. Defaults to value recommended in Hoffman and Gelman (2014).
mu: Value to regularize (log) scale towards. If NULL (the default), mu will be set to log(10 * initial_scale), as recommended in Hoffman and Gelman (2014).

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.

Examples

target_distribution <- list(
  log_density = function(x) -sum(x^2) / 2,
  grad_log_density = function(x) -x
)
proposal <- barker_proposal(target_distribution)
adapter <- dual_averaging_scale_adapter(
  initial_scale = 1., target_accept_prob = 0.4
)
adapter$initialize(proposal, chain_state(c(0, 0)))