Assess quality of interval DR projections — assess

Computes quality and behavior indices for each combination of DR method and interval distance metric. Optionally performs permutation tests for statistical significance.

Usage

assess_quality(
  x,
  projections,
  K = 5,
  metrics = c("Int-Euclidean", "Hausdorff", "Ichino-Yaguchi", "Wasserstein"),
  perm_test = FALSE,
  n_perm = 1000
)

Arguments

x: An interval_data object (standardized).
projections: An idr_projections object from run_idr(), or a named list with the same structure.
K: Integer neighborhood size (default 5).
metrics: Character vector of distance metrics to evaluate.
perm_test: Logical; perform permutation tests (default FALSE).
n_perm: Integer number of permutations (default 1000).

Value

An object of class qaidr_assessment containing:

results: Data frame with columns IDR, Metric, Q_TC, B_TC, Q_RE, B_RE, Q_LC, B_LC.
pvalues: Data frame of p-values (if perm_test = TRUE).
K: The neighborhood size used.

Examples

if (FALSE) { # \dontrun{
data(cars_mm)
x <- standardize(cars_mm)
proj <- run_idr(x)
result <- assess_quality(x, proj, K = 5, perm_test = TRUE)
print(result)
} # }