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Settings to tune a Metropolis-Hastings step
set_mh(adjust_burn = 0.8, acc_target = c(0.2, 0.45), acc_change = 0.01)
Numeric scalar with the percentage of burn-in that should be used to tune the MH step.
Numeric vector with the lower and upper bound of the target acceptance rate for the MH step.
Numeric scalar with the percentage adjustment to the proposal scale for tuning.
Returns a list with settings to tune the Metropolis-Hastings step of a Bayesian model.
# NOT RUN { set_mh(0.5, c(0.1, 0.5), .05) # }
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