likelihood_function {topolow} | R Documentation |
Evaluate Likelihood with Cross-Validation
Description
Calculates cross-validated likelihood for a set of parameters by:
Splitting data into training/validation sets
Fitting model on training data
Evaluating likelihood on validation set
Repeating across folds To calculate one NLL per set of parameters, the function uses a pooled errors approach which combines all validation errors into one set, then calculate a single NLL. This approach has two main advantages: 1- It treats all validation errors equally, respecting the underlying error distribution assumption 2- It properly accounts for the total number of validation points
Usage
likelihood_function(
distance_matrix,
mapping_max_iter,
relative_epsilon,
N,
k0,
cooling_rate,
c_repulsion,
folds = 20,
num_cores = 1
)
Arguments
distance_matrix |
Distance matrix to fit |
mapping_max_iter |
Maximum map optimization iterations |
relative_epsilon |
Convergence threshold |
N |
Number of dimensions |
k0 |
Initial spring constant |
cooling_rate |
Spring constant decay rate |
c_repulsion |
Repulsion constant |
folds |
Number of CV folds |
num_cores |
Number of cores for parallel processing |
Value
List with:
Holdout_MAE |
Mean absolute error on validation data |
NLL |
Negative log likelihood |