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SurvivalPredictResult

gam_models::survival::predict

Struct SurvivalPredictResult 

Source 
pub struct SurvivalPredictResult {
    pub times: Vec<f64>,
    pub hazard: Array2<f64>,
    pub survival: Array2<f64>,
    pub cumulative_hazard: Array2<f64>,
    pub linear_predictor: Array1<f64>,
    pub likelihood_mode: SurvivalLikelihoodMode,
    pub survival_se: Option<Array2<f64>>,
    pub eta_se: Option<Array1<f64>>,
    pub covariance_source: Option<SurvivalPredictionCovarianceMode>,
}
Expand description

Result of predict_survival.

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§times: Vec<f64>§hazard: Array2<f64>§survival: Array2<f64>§cumulative_hazard: Array2<f64>§linear_predictor: Array1<f64>§likelihood_mode: SurvivalLikelihoodMode§survival_se: Option<Array2<f64>>

Per-cell delta-method SE on the survival surface. Same shape as survival. Populated only when the request set with_uncertainty = true and the model class supports it.

§eta_se: Option<Array1<f64>>

Per-row delta-method SE on the linear predictor at the row’s own exit time. Length n. Populated under the same conditions as survival_se.

§covariance_source: Option<SurvivalPredictionCovarianceMode>

Exact coefficient-covariance definition behind survival_se/eta_se. Result-owned provenance (#2296): presenters must serialize this, never the requested mode. None iff the result carries no uncertainty surfaces.

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impl SurvivalPredictResult

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pub fn restricted_mean_survival_time(&self, tau: f64) -> Option<Array1<f64>>

Per-row restricted mean survival time \int_0^{tau} S_i(t) dt from the predicted survival surface. tau is the restriction horizon (e.g. the study follow-up bound). Length-n vector, one RMST per predicted row.

Returns None if the prediction grid is empty, tau <= 0, or any row’s survival curve carries a non-finite value on [0, tau].

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