`zscore_threshold` – Flag observations beyond a z-score threshold.#

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Operational op under axis outlier_policy, sub-layer l2_c, layer l2. Standalone callable: mf.functions.zscore_outlier_clean.

Function signature#

mf.functions.zscore_outlier_clean(
    panel: pd.DataFrame,
) -> pd.DataFrame

Parameters#

name	type	default	constraint	description
`panel`	`pd.DataFrame`	—	—	Input panel. Each column is a variable; rows are time periods. Series is promoted to a single-column DataFrame internally.

Returns#

pd.DataFrame — scalar result.

Behavior#

Computes the rolling z-score per series and flags |z| > leaf_config.zscore_threshold_value (default 3.0). Simpler than IQR but assumes approximately Gaussian residuals.

When to use

Approximately-Gaussian series; quick sanity-check sweeps.

In recipe context#

Set params.outlier_policy = "zscore_threshold" in the relevant layer to activate this op within a recipe:

# Layer L2 recipe fragment
params:
  outlier_policy: zscore_threshold

References#

macroforecast design Part 2, L2: ‘preprocessing is the only layer with a strict A→B→C→D→E execution order; every cell follows the same pipeline.’

zscore_threshold – Flag observations beyond a z-score threshold.#