logL_GP: Log-Likelihood function of a Gaussian Process

In MagmaClustR: Clustering and Prediction using Multi-Task Gaussian Processes with Common Mean

Log-Likelihood function of a Gaussian Process

Description

Log-Likelihood function of a Gaussian Process

Usage

logL_GP(hp, db, mean, kern, post_cov, pen_diag)

Arguments

hp	A tibble, data frame or named vector containing hyper-parameters.
db	A tibble containing the values we want to compute the logL on. Required columns: Input, Output. Additional covariate columns are allowed.
mean	A vector, specifying the mean of the GP at the reference inputs.
kern	A kernel function.
post_cov	(optional) A matrix, corresponding to covariance parameter of the hyper-posterior. Used to compute the hyper-prior distribution of a new individual in Magma.
pen_diag	A jitter term that is added to the covariance matrix to avoid numerical issues when inverting, in cases of nearly singular matrices.

Value

A number, corresponding to the value of Gaussian log-Likelihood (where the covariance can be the sum of the individual and the hyper-posterior's mean process covariances).

Examples

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MagmaClustR documentation built on June 29, 2024, 1:06 a.m.