run_adapt {EMC2} | R Documentation |
Special instance of run_emc
, with default arguments specified for completing adaptation.
run_adapt(
emc,
stop_criteria = NULL,
p_accept = 0.8,
step_size = 100,
verbose = FALSE,
verboseProgress = FALSE,
fileName = NULL,
particles = NULL,
particle_factor = 50,
cores_per_chain = 1,
cores_for_chains = length(emc),
max_tries = 20,
n_blocks = 1
)
emc |
An emc object |
stop_criteria |
A list. Defines the stopping criteria and for which types of parameters these should hold. See |
p_accept |
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 |
step_size |
An integer. After each step, the stopping requirements as
specified by |
verbose |
Logical. Whether to print messages between each step with the current status regarding the stop_criteria. |
verboseProgress |
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. |
fileName |
A string. If specified will autosave emc at this location on every iteration. |
particles |
An integer. How many particles to use, default is |
particle_factor |
An integer. |
cores_per_chain |
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 |
An integer. How many cores to use across chains.
Defaults to the number of chains. the total number of cores used is equal to |
max_tries |
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. |
n_blocks |
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. |
An emc object