Beta-Binomial Conjugate Model: Prior update and posterior predictions for binomial data.
Gamma-Poisson Conjugate Model: Inference on count data.
Normal-Normal Conjugate Model: Continuous data with known variance.
Serialization: ToJson support for model persistence.
Example
///|
test {
// Create a Beta-Binomial model with prior alpha=1.0, beta=1.0 (Uniform prior)
let prior = BetaBinomial::new(1.0, 1.0)
// Update with 7 successes out of 10 trials
let posterior = prior.update(7, 10)
// Posterior mean is now (1+7) / (1+10+1) = 8 / 12 = 0.666...
inspect(posterior.posterior_mean(), content="0.6666666666666666")
}
///|
test {
// Gamma-Poisson model example
let prior = GammaPoisson::new(2.0, 1.0)
let posterior = prior.update(3, 2)
inspect(posterior.posterior_mean(), content="1.6666666666666667")
}
test {
// Normal-Normal model example
let prior = NormalNormal::new(0.0, 1.0, 1.0)
let posterior = prior.update(1.0, 1)
inspect(posterior.posterior_mean(), content="0.5")
}
moon-bayes-kit
MoonBit Composable Bayesian Online Update Library.
Features
ToJsonsupport for model persistence.Example