gr_GP {MagmaClustR} | R Documentation |
Gradient of the logLikelihood of a Gaussian Process
Description
Gradient of the logLikelihood of a Gaussian Process
Usage
gr_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 named vector, corresponding to the value of the hyper-parameters gradients for the 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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