Special instance of run_emc, with default arguments specified for completing burn_in.
Will run both preburn and burn.
auto_burn(
emc,
preburn = 150,
p_accept = 0.8,
step_size = 100,
verbose = FALSE,
verboseProgress = FALSE,
fileName = NULL,
stop_criteria = NULL,
particles = NULL,
particle_factor = 50,
cores_per_chain = 1,
cores_for_chains = length(emc),
max_tries = 20,
n_blocks = 1
)An emc object
An emc object
An integer. The number of iterations run for preburn stage.
A double. The target acceptance probability of the MCMC process. This fine-tunes the width of the search space to obtain the desired acceptance probability. Defaults to .8
An integer. After each step, the stopping requirements as
specified by stop_criteria are checked and proposal distributions are updated. Defaults to 100.
Logical. Whether to print messages between each step with the current status regarding the stop_criteria.
Logical. Whether to print a progress bar within each step or not. Will print one progress bar for each chain and only if cores_for_chains = 1.
A string. If specified will autosave emc at this location on every iteration.
A list. Defines the stopping criteria and for which types of parameters these should hold. See ?fit.
An integer. How many particles to use, default is NULL and particle_factor is used instead.
If specified will override particle_factor.
An integer. particle_factor multiplied by the square root of the number of sampled parameters determines the number of particles used.
An integer. How many cores to use per chain.
Parallelizes across participant calculations. Only available on Linux or Mac OS.
For Windows, only parallelization across chains (cores_for_chains) is available.
An integer. How many cores to use across chains.
Defaults to the number of chains. the total number of cores used is equal to cores_per_chain * cores_for_chains.
An integer. How many times should it try to meet the finish conditions as specified by stop_criteria? Defaults to 20. max_tries is ignored if the required number of iterations has not been reached yet.
An integer. Number of blocks. Will block the parameter chains such that they are updated in blocks. This can be helpful in extremely tough models with a large number of parameters.