Struct BayesianConfidenceUpdater 

pub struct BayesianConfidenceUpdater { /* private fields */ }

Bayesian confidence updater using a Beta-Bernoulli conjugate model.

Model

Maintains parameters (α, β) of a Beta distribution. On each observation:

• Success: α += 1
• Failure: β += 1

The posterior mean α / (α + β) is used as the point estimate.

Implementations

impl BayesianConfidenceUpdater

pub fn new(prior: BetaPrior) -> Self

Create an updater with an explicit prior.

pub fn with_builtin_prior() -> Self

Create an updater with the builtin_priors() prior.

pub fn update_success(&mut self)

Record a success observation (α += 1).

pub fn update_failure(&mut self)

Record a failure observation (β += 1).

pub fn update(&mut self, successes: u32, failures: u32)

Apply successes and failures in bulk.

pub fn posterior_mean(&self) -> f32

Posterior mean: α / (α + β).

pub fn posterior_variance(&self) -> f32

Posterior variance: αβ / ((α+β)²(α+β+1)).

pub fn sample_count(&self, prior: &BetaPrior) -> u32

Total observations recorded above the prior (i.e. (α - α₀) + (β - β₀)).

pub fn snapshot(&self, prior: &BetaPrior) -> ConfidenceSnapshot

Build a ConfidenceSnapshot from the current posterior state.

prior is used only to compute sample_count; pass builtin_priors() unless you constructed this updater with a custom prior.

pub fn alpha(&self) -> f32

Current alpha parameter (useful for serialisation/inspection).

pub fn beta(&self) -> f32

Current beta parameter (useful for serialisation/inspection).