General simulation parameters
Population size
Total size of the synthetic population.
Number of variables
Number of predictors in the synthetic population.
Dependence
Correlation strength between predictors.
Dependent share
Proportion of dependent predictors.
Sparsity
Share of coefficients that are zero.
Coefficient mean
Mean of the regression coefficients.
Coefficient SD
Standard deviation of the coefficients.
Target R²
Desired R² of the fitted model.
Model type
Type of model used in the simulation.
Performance metric
Metric to optimise.
Min sample size
Minimal sample size.
Max sample size
Maximal sample size.
Step size
Increment between sample sizes.
Repetitions
Number of Monte-Carlo repetitions per sample size.
Convergence threshold
Stop when metric improvement is below this value.
Number of consecutive sample sizes for convergence
How many consecutive sample sizes that produce a model within the desired treshold are required for convergence.
Advanced simulation input
Population size
Total size of the synthetic population.
Number of variables
Number of predictors in the synthetic population.
Dependence
Correlation strength between predictors.
Dependent share
Proportion of dependent predictors.
Sparsity
Share of coefficients that are zero.
Coefficient mean
Mean of the regression coefficients.
Coefficient SD
Standard deviation of the coefficients.
Target R²
Desired R² of the fitted model.
Model type
Type of model used in the simulation.
Performance metric
Metric to optimise.
Min sample size
Minimal sample size.
Max sample size
Maximal sample size.
Step size
Increment between sample sizes.
Repetitions
Number of Monte-Carlo repetitions per sample size.
Convergence threshold
Stop when metric improvement is below this value.
Number of consecutive sample sizes for convergence
How many consecutive sample sizes that produce a model within the desired treshold are required for convergence.