| NuggetKM-class | R Documentation |
"km" ClassThis class is intended to be used either by using its
own dedicated S4 methods or by using the S4 methods inherited
from the "km" class of the libKriging package.
d,n,X,y,p,FNumber of (numeric) inputs, number of observations, design matrix, response vector, number of trend variables, trend matrix.
trend.formula,trend.coefFormula used for the trend, vector
\hat{\boldsymbol{\beta}} of estimated (or fixed)
trend coefficients with length p.
covarianceA S4 object with class "covTensorProduct"
representing a covariance kernel.
noise.flag,noise.varLogical flag and numeric value for an optional noise term.
known.paramA character code indicating what parameters are known.
lower,upperBounds on the correlation range parameters.
method,penalty,optim.method,control,gr,parinitObjects defining the estimation criterion, the optimization.
T,M,zAuxiliary variables (matrices and vectors) that can be used in several computations.
caseThe possible concentration (a.k.a. profiling) of the likelihood.
param.estimLogical. Is an estimation used?
NuggetKrigingA copy of the NuggetKriging object used to create
the current NuggetKM object.
Yann Richet yann.richet@asnr.fr
km-class in the
DiceKriging package. The creator NuggetKM.
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