TermsPredictionResult

Container returned by GAM.predict(type="terms").

Usage

Source

TermsPredictionResult(
    terms,
    se,
    labels=list(),
)

Instead of collapsing every smooth’s effect into a single linear predictor, each smooth term’s contribution is kept separate. This is useful for decomposing a fitted additive model into its constituent partial effects (e.g., to inspect how much of the prediction at a point comes from s(x1) versus s(x2)) without needing to build partial-effect plots.

Attributes

terms: dict[str, numpy.ndarray]

Maps each term label (e.g. "s(x1)", "te(x1, x2)", or "s(x1):group_a" for factor-by smooths) to that term’s contribution to the linear predictor, each of shape (n,). Contributions sum (plus the intercept and any parametric terms) to the full linear predictor.

se: dict[str, numpy.ndarray] or None

Maps each term label to its per-term standard error, each of shape (n,). None unless se=True was passed to predict().

labels: list[str]

Term labels in formula order, matching the keys of terms and se.

Attributes

Name	Description
values	Sum of all term contributions (overall linear predictor).

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values

Sum of all term contributions (overall linear predictor).

values: NDArray