Permutation test for an effect operator

Usage

# S3 method for class 'effect_operator'
perm_test(
  x,
  nperm = 999,
  scheme = c("reduced_model"),
  parallel = FALSE,
  alpha = 0.05,
  stepwise = TRUE,
  alternative = c("greater", "less", "two.sided"),
  refit_basis = FALSE,
  seed = NULL,
  ...
)

Arguments

x: An effect_operator.
nperm: Number of permutations.
scheme: Permutation scheme. Currently only "reduced_model" is supported.
parallel: Logical; if TRUE, use future.apply.
alpha: Sequential significance threshold used to determine selected rank.
stepwise: Logical; if TRUE, apply sequential rank testing by deflating previously selected effect directions before evaluating the next axis.
alternative: Alternative hypothesis for empirical p-values. Only "greater" is supported for effect-operator permutation tests.
refit_basis: Logical; if TRUE, refit the feature basis per permutation from that permutation's reduced-model residual (and refit the observed basis from the observed reduced-model residual). Uses the full whitened feature space. Keeps the same basis rank as the static fit. Experimental; intended for evaluating whether static-basis leakage drives miscalibration.
seed: Optional integer seed for reproducibility.
...: Reserved for future extensions.

Value

A permutation-test result object for effect operators.