Struct BayesianFosrResult 

#[non_exhaustive]
pub struct BayesianFosrResult {
    pub beta_mean: FdMatrix,
    pub beta_lower: FdMatrix,
    pub beta_upper: FdMatrix,
    pub fitted: FdMatrix,
    pub residuals: FdMatrix,
    pub sigma2_mean: Vec<f64>,
    pub n_iter: usize,
    pub burn_in: usize,
    pub thin: usize,
    pub ncomp: usize,
}

Result of Bayesian function-on-scalar regression via conjugate Gibbs (REG-06-04).

Posterior summaries are computed from thinned post-burn-in draws. Credible bands are pointwise (not simultaneous) quantiles over the retained draws.

Divergence from refund: uses FPCA score compression via fdata_to_pc_1d rather than spline basis priors. Pointwise credible bands only (no simultaneous bands).

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

beta_mean: FdMatrix

Posterior mean coefficient functions β̄(t) (p × m_t).

beta_lower: FdMatrix

Pointwise 2.5% credible band (p × m_t).

beta_upper: FdMatrix

Pointwise 97.5% credible band (p × m_t).

fitted: FdMatrix

Posterior-mean fitted values (n × m_t).

residuals: FdMatrix

Posterior-mean residuals (n × m_t).

sigma2_mean: Vec<f64>

Posterior mean σ²(t) across the response grid (length m_t).

n_iter: usize

Number of Gibbs iterations retained (after burn-in, before thinning).

burn_in: usize

Burn-in iterations discarded.

thin: usize

Thinning interval used.

ncomp: usize

FPC components used for score compression.

Trait Implementations

impl Clone for BayesianFosrResult

fn clone(&self) -> BayesianFosrResult

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for BayesianFosrResult

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

Formats the value using the given formatter.

impl PartialEq for BayesianFosrResult

fn eq(&self, other: &BayesianFosrResult) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl StructuralPartialEq for BayesianFosrResult