covStruct.create: Spatial covariance - Class constructor

Description Usage Arguments Value Author(s) See Also

Description

Creates a covariance structure.

Usage

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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)

Arguments

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

Value

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).

Author(s)

O. Roustant, D. Ginsbourger

See Also

km


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