logLik

0th

Percentile

log-likelihood of a km object

Returns the log-likelihood value of a km object.

Keywords
models
Usage
# S4 method for km
logLik(object, ...)
Arguments
object

an object of class km containing the trend and covariance structures.

...

no other argument for this method.

Value

The log likelihood value.

References

N.A.C. Cressie (1993), Statistics for spatial data, Wiley series in probability and mathematical statistics.

D. Ginsbourger, D. Dupuy, A. Badea, O. Roustant, and L. Carraro (2009), A note on the choice and the estimation of kriging models for the analysis of deterministic computer experiments, Applied Stochastic Models for Business and Industry, 25 no. 2, 115-131.

R. Li and A. Sudjianto (2005), Analysis of Computer Experiments Using Penalized Likelihood in Gaussian Kriging Models, Technometrics, 47 no. 2, 111-120.

K.V. Mardia and R.J. Marshall (1984), Maximum likelihood estimation of models for residual covariance in spatial regression, Biometrika, 71, 135-146.

J.D. Martin and T.W. Simpson (2005), Use of kriging models to approximate deterministic computer models, AIAA Journal, 43 no. 4, 853-863.

J.-S. Park and J. Baek (2001), Efficient computation of maximum likelihood estimators in a spatial linear model with power exponential covariogram, Computer Geosciences, 27 no. 1, 1-7.

C.E. Rasmussen and C.K.I. Williams (2006), Gaussian Processes for Machine Learning, the MIT Press, http://www.GaussianProcess.org/gpml

J. Sacks, W.J. Welch, T.J. Mitchell, and H.P. Wynn (1989), Design and analysis of computer experiments, Statistical Science, 4, 409-435.

M.L. Stein (1999), Interpolation of spatial data, some theory for kriging, Springer.

See Also

km, logLikFun

Aliases
  • logLik
  • logLik.km
  • logLik,km-method
Documentation reproduced from package DiceKriging, version 1.5.6, License: GPL-2 | GPL-3

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