adaptive_MC_sampling {topolow} | R Documentation |
Perform Adaptive Monte Carlo Sampling
Description
Main function implementing adaptive Monte Carlo sampling to explore parameter space.
Updates sampling distribution based on evaluated likelihoods. This is an internal
function called by run_adaptive_sampling
.
Usage
adaptive_MC_sampling(
samples_file,
distance_matrix,
iterations = 1,
batch_size = 1,
mapping_max_iter,
relative_epsilon,
folds = 20,
num_cores = 1,
scenario_name,
verbose = FALSE
)
Arguments
samples_file |
Path to CSV with initial samples for this job. |
distance_matrix |
Distance matrix to fit |
iterations |
Number of sampling iterations per job |
batch_size |
Samples per iteration (fixed to 1) |
mapping_max_iter |
Maximum map optimization iterations |
relative_epsilon |
Convergence threshold |
folds |
Number of CV folds |
num_cores |
Number of cores for parallel processing |
scenario_name |
Name for output files |
verbose |
Logical. Whether to print progress messages. Default: FALSE |
Value
A data.frame
containing all samples (initial and newly generated)
with their parameters and evaluated performance metrics. The data frame includes
columns for the log-transformed parameters, Holdout_MAE
, and NLL
.
Returns NULL
if the results file was not created.