package gpr

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Module type
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Sub-modules for learning without derivatives.

module Spec = Spec.Eval

Specification of covariance function

module Inducing = FITC.Eval.Inducing

Evaluating inducing inputs

module Input = FITC.Eval.Input

Evaluating single inputs

module Inputs = FITC.Eval.Inputs

Evaluating (multiple) inputs

module Model = FITC.Eval.Model

(Untrained) model - does not require targets

module Trained = FITC.Eval.Trained

Trained model - requires targets

module Stats : sig ... end

Statistics derived from trained models

module Mean_predictor = FITC.Eval.Mean_predictor

Module for making mean predictions

module Mean = FITC.Eval.Mean

Posterior mean for a single input

module Means = FITC.Eval.Means

Posterior means for (multiple) inputs

module Co_variance_predictor = FITC.Eval.Co_variance_predictor

Module for making (co-)variance predictions

module Variance = FITC.Eval.Variance

Posterior variance for a single input

module Variances = FITC.Eval.Variances

Posterior variances for (multiple) inputs

module Covariances : sig ... end

Posterior covariances

module Sampler = FITC.Eval.Sampler

Module for sampling single points from the posterior distribution

module Cov_sampler : sig ... end

Module for sampling (multiple) points from the posterior distribution accounting for their covariance