migration_crossover: Perform a Migration Step Between Chains

In dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models

Perform a Migration Step Between Chains

Description

In a migration step, a random subset of chains is selected. Each selected chain k receives a proposal based on the next chain (k + 1) in the sequence (cycling back to the first chain after the last). The proposed parameters are slightly perturbed by uniform noise controlled by b. All proposals are then evaluated simultaneously using Metropolis acceptance probabilities via call_log_posterior_m(), and accepted proposals replace the current values.

Usage

migration_crossover(
  prms_across_chains,
  pis_across_chains,
  log_likes_across_chains,
  b = 0.001,
  ...
)

Arguments

prms_across_chains	a numeric matrix of dimension ⁠p × n⁠, where p is the number of parameters and n is the number of chains. Each column contains the current parameter vector of a chain.
pis_across_chains	a numeric vector of length n, containing the current log-posterior values for each chain.
log_likes_across_chains	a numeric vector of length n, containing the current log-likelihood values for each chain.
b	a small numeric value used to perturb the proposal parameters to avoid degeneracy.
...	additional arguments passed to call_log_posterior_m().

Value

A list with the following components:

• new_prms_across_chains: The updated parameter matrix of shape ⁠p × n⁠.

• new_pis_across_chains: The updated vector of log-posterior values.

• new_log_likes_across_chains: The updated vector of log-likelihood values.

See Also

full_crossover, call_log_posterior_m()

dRiftDM documentation built on Dec. 1, 2025, 5:08 p.m.