Score the ECOD + COPOD novelty discriminator — score_ecod

Scores each row of X independently with the frozen model from fit_ecod_copod. For one specimen the abundances are mapped to the per-sample robust CLR over its own positive support; its ECOD and COPOD tail aggregates are computed in pure R against the frozen per-feature control reference ECDFs (never pyod); each aggregate is z-standardized with the frozen control mean / sd, the two z-scores are averaged, and the frozen orientation is applied so larger = more case-like.

The present feature set is intersect(model$feature_universe, colnames(X)); features missing from a specimen contribute no tail term. If fewer than model$hp$min_features universe features are present, the neutral score 0 is returned for every row. The score of a row depends only on that row and the frozen model, and is exactly invariant to per-specimen scaling.

Usage

score_ecod_copod(model, X, meta = NULL)

Arguments

model: An ecod_copod_model object from fit_ecod_copod.
X: Numeric matrix (samples $\times$ features) of non-negative abundances with named feature columns.
meta: Optional per-sample metadata. Accepted for interface uniformity and ignored by this method.

Value

Plain finite numeric vector of length nrow(X); larger values are more case-like.

Examples

if (FALSE) { # \dontrun{
model <- fit_ecod_copod(X, y)
score_ecod_copod(model, X[1, , drop = FALSE])
} # }