FactorSmoothResult

class superglm.FactorSmoothResult(

name: str,

variable: str,

grouping_variable: str,

basis: Literal['fs', 'sz'],

lambdas: dict[str, float],

phi: float,

variance_components: dict[str, float],

effective_df: float,

collapsed: bool | None,

at_lower_boundary: dict[str, bool],

at_upper_boundary: dict[str, bool],

table: DataFrame,

curves: DataFrame,

diagnostics: dict[str, Any],

)

Bases: object

Shared smoothing parameters and fitted level curves.

Fully penalized fs reports include local credibility diagnostics. Sum-to-zero sz reports instead describe centered deviation curves.

property smoothing_lambdas: dict[str, float]

Named alias emphasizing that lambdas are shared across all levels.