Struct FitConfig 

pub struct FitConfig {

    pub family: Option<String>,
    pub link: Option<String>,
    pub flexible_link: bool,
    pub offset_column: Option<String>,
    pub noise_offset_column: Option<String>,
    pub frailty: Option<FrailtySpec>,
    pub baseline_target: String,
    pub baseline_scale: Option<f64>,
    pub baseline_shape: Option<f64>,
    pub baseline_rate: Option<f64>,
    pub baseline_makeham: Option<f64>,
    pub time_basis: String,
    pub time_degree: usize,
    pub time_num_internal_knots: usize,
    pub time_smooth_lambda: f64,
    pub survival_likelihood: String,
    pub survival_distribution: String,
    pub threshold_time_k: Option<usize>,
    pub threshold_time_degree: usize,
    pub sigma_time_k: Option<usize>,
    pub sigma_time_degree: usize,
    pub noise_formula: Option<String>,
    pub logslope_formula: Option<String>,
    pub z_column: Option<String>,
    pub weight_column: Option<String>,
    pub scale_dimensions: bool,
    pub ridge_lambda: f64,
    pub transformation_normal: bool,
    pub firth: bool,
    pub resource_policy: Option<ResourcePolicy>,
}

Non-formula configuration for model fitting. All fields have sensible defaults.

Fields

family: Option<String>

Family: “gaussian”, “binomial”, “poisson”, “gamma”, or None for auto-detect.

link: Option<String>

Link: “identity”, “logit”, “probit”, “cloglog”, “sas”, “beta-logistic”, or None.

flexible_link: bool

Whether to use flexible (wiggle-augmented) link.

offset_column: Option<String>

Optional additive offset column for the primary linear predictor.

noise_offset_column: Option<String>

Optional additive offset column for the noise/log-scale predictor.

frailty: Option<FrailtySpec>

Optional family-level frailty modifier.

baseline_target: String

Baseline target: “linear”, “weibull”, “gompertz”, “gompertz-makeham”.

baseline_scale: Option<f64>

baseline_shape: Option<f64>

baseline_rate: Option<f64>

baseline_makeham: Option<f64>

time_basis: String

Time basis: “ispline” or “none”.

time_degree: usize

time_num_internal_knots: usize

time_smooth_lambda: f64

survival_likelihood: String

Survival likelihood mode: “location-scale”, “transformation”, “weibull”, “marginal-slope”, “latent”, or “latent-binary”.

survival_distribution: String

Residual distribution: “gaussian”, “logistic”, “gumbel”.

threshold_time_k: Option<usize>

threshold_time_degree: usize

sigma_time_k: Option<usize>

sigma_time_degree: usize

noise_formula: Option<String>

If set, fit a location-scale model with this formula for the noise parameter.

logslope_formula: Option<String>

Formula for the log-slope model (survival marginal-slope or Bernoulli marginal-slope).

z_column: Option<String>

Column name for the z (exposure/dose) variable in marginal-slope models.

weight_column: Option<String>

Optional non-negative per-row training weights column.

scale_dimensions: bool

ridge_lambda: f64

transformation_normal: bool

Route the fit through the transformation-normal family. When set, the formula terms are treated as the covariate side of the transformation model and the response basis is built internally. Incompatible with noise_formula and with Surv(...) responses.

firth: bool

Enable Firth bias reduction for standard single-parameter families.

resource_policy: Option<ResourcePolicy>

Optional override of the crate::resource::ResourcePolicy used when planning spatial bases (TPS / Matern / Duchon) during term construction. When None, the default-library policy is used.

Trait Implementations

impl Clone for FitConfig

fn clone(&self) -> FitConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for FitConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for FitConfig

fn default() -> Self

Returns the “default value” for a type.