logLikFun: Log-Likelihood of a Gaussian Process.

In lineqGPR: Gaussian Process Regression Models with Linear Inequality Constraints

Description

Compute the negative log-likelihood of a Gaussian Process.

Usage

logLikFun(
  par = model$kernParam$par,
  model,
  parfixed = NULL,
  mcmc.opts = NULL,
  estim.varnoise = FALSE
)

Arguments

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

Value

The value of the negative log-likelihood.

Author(s)

A. F. Lopez-Lopera.

References

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

See Also

logLikGrad, constrlogLikFun, constrlogLikGrad

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