logLikGrad: Concentrated log-Likelihood of a km object - Analytical...
In DiceKriging: Kriging Methods for Computer Experiments
Description
Usage
Arguments
Value
Author(s)
References
See Also
Description
Returns the exact gradient vector of the concentrated log-likelihood.
Usage
1
logLikGrad(param, model, envir)
Arguments
param
a vector containing the optimization variables.
model
an object of class km.
envir
an environment specifying where to get intermediate values calculated in logLikFun.
Value
the gradient of the concentrated log-likelihood.
Author(s)
O. Roustant, D. Ginsbourger, Ecole des Mines de St-Etienne
References
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.
See Also
DiceKriging documentation built on Feb. 24, 2021, 1:07 a.m.
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Description Usage Arguments Value Author(s) References See Also
Description
Returns the exact gradient vector of the concentrated log-likelihood.
Usage
1 | logLikGrad(param, model, envir)
|
Arguments
param |
a vector containing the optimization variables. |
model |
an object of class |
envir |
an environment specifying where to get intermediate values calculated in |
Value
the gradient of the concentrated log-likelihood.
Author(s)
O. Roustant, D. Ginsbourger, Ecole des Mines de St-Etienne
References
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.
See Also
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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