Run the simulation workflows used in the article and thesis.
Usage
run_simulation_study(
dimensions = list(c(500L, 100L), c(500L, 20L), c(100L, 20L), c(80L, 25L), c(60L, 33L),
c(40L, 50L), c(20L, 100L)),
true_ncomp = c(2L, 4L, 6L),
missing_props = seq(5, 50, 5),
mechanisms = c("MCAR", "MAR"),
reps = 1L,
seed = NULL,
max_ncomp = 8L,
criteria = c("Q2-LOO", "Q2-10fold", "AIC", "AIC-DoF", "BIC", "BIC-DoF"),
incomplete_methods = c("nipals_standard", "nipals_adaptative"),
imputation_methods = c("mice", "knn", "svd"),
folds = 10L,
mar_y_bias = 0.8
)Arguments
- dimensions
List of
(n, p)integer pairs.- true_ncomp
Vector of true component counts.
- missing_props
Missing-data proportions as fractions or percentages.
- mechanisms
Missing-data mechanisms.
- reps
Number of replicates.
- seed
Optional base random seed.
- max_ncomp
Maximum number of extracted components.
- criteria
Criteria evaluated on complete and imputed data.
- incomplete_methods
Incomplete-data NIPALS workflows.
- imputation_methods
Imputation methods.
- folds
Number of folds used by
"Q2-10fold".- mar_y_bias
MAR bias parameter passed to
add_missingness().