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