logL_GP_mod {MagmaClustR} | R Documentation |
Modified log-Likelihood function for GPs
Description
Log-Likelihood function involved in Magma during the maximisation step of the training. The log-Likelihood is defined as a simple Gaussian likelihood added with correction trace term.
Usage
logL_GP_mod(hp, db, mean, kern, post_cov, pen_diag)
Arguments
hp |
A tibble, data frame or named vector of hyper-parameters. |
db |
A tibble containing values we want to compute 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 |
A matrix, covariance parameter of the hyper-posterior. Used to compute the correction term. |
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 the modified Gaussian log-Likelihood defined in Magma.
Examples
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