pub struct BernoulliMarginalSlopeInputs<'a> {Show 18 fields
pub formula: String,
pub data_schema: DataSchema,
pub logslope_formula: String,
pub z_column: String,
pub resolved_marginalspec: TermCollectionSpec,
pub resolved_logslopespec: TermCollectionSpec,
pub fit_result: UnifiedFitResult,
pub p_marginal: usize,
pub baseline_marginal: f64,
pub baseline_logslope: f64,
pub latent_z_normalization: SavedLatentZNormalization,
pub latent_measure: LatentMeasureKind,
pub latent_z_rank_int_calibration: Option<LatentZRankIntCalibration>,
pub latent_z_conditional_calibration: Option<LatentZConditionalCalibration>,
pub score_warp_runtime: Option<&'a DeviationRuntime>,
pub link_dev_runtime: Option<&'a DeviationRuntime>,
pub base_link: InverseLink,
pub frailty: FrailtySpec,
}Expand description
The resolved, source-agnostic semantic content of a Bernoulli marginal-slope saved model.
The CLI threads these in directly from its fit pipeline; the FFI produces
them by freezing its term collections and reading the [FitConfig]. Either
way, the assembler below turns them into the canonical payload.
Fields§
§formula: String§data_schema: DataSchema§logslope_formula: String§z_column: String§resolved_marginalspec: TermCollectionSpec§resolved_logslopespec: TermCollectionSpec§fit_result: UnifiedFitResult§p_marginal: usizeNumber of raw marginal design columns p_m (= the term-collection
marginal design’s ncols() BEFORE any #461 influence-absorber widening).
When the Stage-1 influence absorber is active (A2), the fitted marginal
block carries the widened coefficient [β_m; γ] (length p_m + p₁) and
the joint covariance is dimensioned over the widened block. The absorbed
influence columns Z̃_infl are a TRAINING-only leakage absorber that does
not exist at predict rows, so the persisted model must drop γ and the
marginalized-out covariance sub-block to stay self-consistent against the
raw p_m marginal design at predict. The assembler uses this to truncate
the fit result once (shared CLI + FFI). With no absorber it equals the
fitted block width and the truncation is a no-op.
baseline_marginal: f64§baseline_logslope: f64§latent_z_normalization: SavedLatentZNormalization§latent_measure: LatentMeasureKind§latent_z_rank_int_calibration: Option<LatentZRankIntCalibration>§latent_z_conditional_calibration: Option<LatentZConditionalCalibration>§score_warp_runtime: Option<&'a DeviationRuntime>§link_dev_runtime: Option<&'a DeviationRuntime>§base_link: InverseLink§frailty: FrailtySpecAuto Trait Implementations§
impl<'a> !RefUnwindSafe for BernoulliMarginalSlopeInputs<'a>
impl<'a> !UnwindSafe for BernoulliMarginalSlopeInputs<'a>
impl<'a> Freeze for BernoulliMarginalSlopeInputs<'a>
impl<'a> Send for BernoulliMarginalSlopeInputs<'a>
impl<'a> Sync for BernoulliMarginalSlopeInputs<'a>
impl<'a> Unpin for BernoulliMarginalSlopeInputs<'a>
impl<'a> UnsafeUnpin for BernoulliMarginalSlopeInputs<'a>
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