This class is intended to be used either by using its
own dedicated S4 methods or by using the S4 methods inherited
"km" class of the libKriging package.
Number of (numeric) inputs, number of observations, design matrix, response vector, number of trend variables, trend matrix.
Formula used for the trend, vector betaHat of estimated (or fixed) trend coefficients with length p.
A S4 object with class
representing a covariance kernel.
Logical flag and numeric value for an optional noise term.
A character code indicating what parameters are known.
Bounds on the correlation range parameters.
Objects defining the estimation criterion, the optimization.
Auxiliary variables (matrices and vectors) that can be used in several computations.
The possible concentration (a.k.a. profiling) of the likelihood.
Logical. Is an estimation used?
A copy of the
NoiseKriging object used to create
Yann Richet firstname.lastname@example.org
km-class in the
DiceKriging package. The creator
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