NuggetKM-class: S4 class for NuggetKriging Models Extending the '"km"' Class

NuggetKM-classR Documentation

S4 class for NuggetKriging Models Extending the "km" Class

Description

This 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.

Slots

d,n,X,y,p,F

Number of (numeric) inputs, number of observations, design matrix, response vector, number of trend variables, trend matrix.

trend.formula,trend.coef

Formula used for the trend, vector betaHat of estimated (or fixed) trend coefficients with length p.

covariance

A S4 object with class "covTensorProduct" representing a covariance kernel.

noise.flag,noise.var

Logical flag and numeric value for an optional noise term.

known.param

A character code indicating what parameters are known.

lower,upper

Bounds on the correlation range parameters.

method,penalty,optim.method,control,gr,parinit

Objects defining the estimation criterion, the optimization.

T,M,z

Auxiliary variables (matrices and vectors) that can be used in several computations.

case

The possible concentration (a.k.a. profiling) of the likelihood.

param.estim

Logical. Is an estimation used?

NuggetKriging

A copy of the NuggetKriging object used to create the current NuggetKM object.

Author(s)

Yann Richet yann.richet@irsn.fr

See Also

km-class in the DiceKriging package. The creator NuggetKM.


rlibkriging documentation built on Sept. 22, 2022, 5:07 p.m.