logLikAdditiveFun: Log-Likelihood of a Additive Gaussian Process.
In lineqGPR: Gaussian Process Regression Models with Linear Inequality Constraints

Description Usage Arguments Value Author(s) References See Also

Compute the negative log-likelihood of an Additive Gaussian Process.

logLikAdditiveFun(
  par = unlist(purrr::map(model$kernParam, "par")),
  model,
  parfixed = NULL,
  mcmc.opts = NULL,
  estim.varnoise = FALSE
)

`par`	the values of the covariance parameters.
`model`	an object with `"lineqAGP"` S3 class.
`parfixed`	not used.
`mcmc.opts`	not used.
`estim.varnoise`	If `true`, a noise variance is estimated.

The value of the negative log-likelihood.

A. F. Lopez-Lopera.

Rasmussen, C. E. and Williams, C. K. I. (2005), "Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)". The MIT Press. [link]

logLikAdditiveGrad

lineqGPR documentation built on Jan. 11, 2020, 9:23 a.m.