covStruct.create: Spatial covariance - Class constructor
In DiceKriging: Kriging Methods for Computer Experiments

Description Usage Arguments Value Author(s) See Also

Creates a covariance structure.

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covStruct.create(covtype, d, known.covparam, var.names, coef.cov = NULL, coef.var = NULL, 
     nugget = NULL, nugget.estim = FALSE, nugget.flag = FALSE,
     iso = FALSE, scaling = FALSE, knots=NULL, kernel=NULL)

`covtype`	a character string specifying the covariance structure.
`d`	an integer containing the spatial dimension.
`known.covparam`	a character ("None" or "All") indicating whether covariance parameters are known or must be estimated.
`var.names`	a vector of character strings containing the variable names.
`coef.cov`	an optional vector containing the values for covariance parameters.
`coef.var`	an optional number containing the variance value.
`nugget`	an optional variance value standing for the homogenous nugget effect. Default is NULL.
`nugget.estim`	is the nugget effect estimated or known?
`nugget.flag`	is there a nugget effect?
`iso`	an optional boolean that can be used to force a tensor-product covariance structure to have a range parameter common to all dimensions.
`scaling`	an optional boolean indicating whether a scaling on the covariance structure should be used.
`knots`	an optional list of knots (used if `scaling = TRUE`)
`kernel`	an optional function containing a new covariance structure

A formal S4 class of type covTensorProduct-class, covIso-class (if iso is TRUE) (if scaling is TRUE), or covUser-class (if kernel is TRUE).

O. Roustant, D. Ginsbourger

km

DiceKriging documentation built on Feb. 24, 2021, 1:07 a.m.