set_mh function

Settings to tune a Metropolis-Hastings step

Settings to tune a Metropolis-Hastings step

set_mh(adjust_burn = 0.8, acc_target = c(0.2, 0.45), acc_change = 0.01)

Arguments

  • adjust_burn: Numeric scalar with the percentage of burn-in that should be used to tune the MH step.
  • acc_target: Numeric vector with the lower and upper bound of the target acceptance rate for the MH step.
  • acc_change: Numeric scalar with the percentage adjustment to the proposal scale for tuning.

Returns

Returns a list with settings to tune the Metropolis-Hastings step of a Bayesian model.

Examples

set_mh(0.5, c(0.1, 0.5), .05)
  • Maintainer: Nikolas Kuschnig
  • License: GPL-3 | file LICENSE
  • Last published: 2022-02-25

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