kumulant/com.eignex.kumulant.stat.regression.glm/PointPosterior

PointPosterior

@Serializable

@SerialName(value = "PointPosterior")

data object PointPosterior : LinearPosterior<StochasticRegressionResult> (source)

Point estimate plus optional isotropic Gaussian noise. SGD models have no posterior variance to draw from; exploration adds a constant std-dev shake on top of the point estimate.

Functions

evaluate

open override fun evaluate(snapshot: StochasticRegressionResult, x: VectorView, rng: Random, exploration: Double = 1.0): Double

Closes to predict(x) + sd * ||x|| * N(0,1) since the per-coord noise terms are iid; one Gaussian draw instead of one per coordinate.

sample

open override fun sample(snapshot: StochasticRegressionResult, rng: Random, exploration: Double = 1.0): VectorView

Draw a weight vector from the posterior at exploration variance scale. exploration = 0.0 collapses to the point estimate; 1.0 is the calibrated posterior.

evaluate

open override fun evaluate(snapshot: StochasticRegressionResult, x: VectorView, rng: Random, exploration: Double = 1.0): Double(source)

Closes to predict(x) + sd * ||x|| * N(0,1) since the per-coord noise terms are iid; one Gaussian draw instead of one per coordinate.

sample

open override fun sample(snapshot: StochasticRegressionResult, rng: Random, exploration: Double = 1.0): VectorView(source)

Draw a weight vector from the posterior at exploration variance scale. exploration = 0.0 collapses to the point estimate; 1.0 is the calibrated posterior.