Function to generate isotropic covariance models, or add an
isotropic covariance
model to an existing isotropic model
Usage
covmodel(modelname, mev, nugget,variance, scale,
parameter, add.covmodel)
## S3 method for class 'covmodel'
print(x, ...)
Arguments
modelname
character vector, name of the covariance model, e.g. "exponential",
"spherical", "gauss". A call of covmodel() without a function argument
displays a table with all available models and their parameters. Check
the CovarianceFct in the RandomFields package for detailed
information about the covariance functions.
mev
numeric value, variance of the measurement error
nugget
numeric value, variance of microstructure white noise process (range smaller than the data support)
variance
numeric value, partial sill of the variogram model
scale
numeric value, scale parameter of the variogram model
parameter
numeric vector of covariance parameters, missing for some model
like nugget, spherical or gauss or
add.covmodel
object of the class covmodel that is
added to the covariance model defined by modelname (see
examples)
x
a covariance model generated by covmodel
...
further printing arguments
Value
an object of the class covmodel that define a covariance model.
Note
The names and parametrisation of the covariance model originate
from the CovarianceFct in the RandomFields package. The
values of the arguments mev, nugget, variance and scale
are by default = 0.
Please, be aware that you only can generate spatial isotropic covariance
models, Time-Space models or so called (hypermodels) are not implemented.