package gpr

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Posterior covariances

type t

Type of covariances

val calc_model_inputs : Model.t -> t

calc_model_inputs model

  • returns

    covariances for all inputs used in model. This may be extremely expensive (O(N^2)) for large numbers of model inputs.

val calc : Co_variance_predictor.t -> sigma2:float -> Inputs.t -> t

calc co_variance_predictor ~sigma2 inputs

  • returns

    posterior covariances for inputs given co_variance_predictor and noise level sigma2. This may be extremely expensive (O(N^2)) for large numbers of inputs.

val get : ?predictive:bool -> t -> Lacaml.D.mat

get ?predictive covariances

  • returns

    the covariances as a matrix. If predictive is true, then the noise level will be added (to the diagonal only).

  • parameter predictive

    default = true

val get_variances : t -> Variances.t

get_variances covariances

  • returns

    the variances in covariances.

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