HasGP.Covariance.Basic
Description
Gaussian Process Library. This module contains assorted functions that support the computation of covariance, constructing covariance matrices etc.
Covariance functions store log parameters. Functions are needed to return the covariance and its derivative. Derivatives are with respect to the actual parameters, NOT their logs.
Copyright (C) 2011 Sean Holden. sbh11@cl.cam.ac.uk.
- class CovarianceFunction a where
- trueHyper :: a -> DVector
- covariance :: a -> DVector -> DVector -> Double
- dCovarianceDParameters :: a -> DVector -> DVector -> DVector
- makeCovarianceFromList :: a -> [Double] -> a
- makeListFromCovariance :: a -> [Double]
- covarianceMatrix :: CovarianceFunction c => c -> Inputs -> CovarianceMatrix
- covarianceWithPoint :: CovarianceFunction c => c -> Inputs -> Input -> DVector
- covarianceWithPoints :: CovarianceFunction c => c -> Inputs -> [Input] -> [DVector]
Documentation
class CovarianceFunction a where
Methods
The actual hyperparameter values.
The covariance
covariance :: a -> DVector -> DVector -> Double
Derivative of covariance with respect to parameters
dCovarianceDParameters :: a -> DVector -> DVector -> DVector
Construct using log parameters.
makeCovarianceFromList :: a -> [Double] -> a
Get log parameters.
makeListFromCovariance :: a -> [Double]
covarianceMatrix :: CovarianceFunction c => c -> Inputs -> CovarianceMatrix
Construct a matrix of covariances from a covariance and a design matrix.
covarianceWithPoint :: CovarianceFunction c => c -> Inputs -> Input -> DVector
Constructs the column vector required when a new input is included. Constructed as a matrix to avoid further work elsewhere.
covarianceWithPoints :: CovarianceFunction c => c -> Inputs -> [Input] -> [DVector]
covarianceWithPoint applied to a list of points to produce a list of vectors.