Class RMmodelgenerator
Objects should not be created by the user!
.Data:function; the genuine function that generates an
object of class
RMmodel
type:character string; specifies the category of RMmodel-function, see Details
domain:character string; specifies whether the corresponding function(s) depend on 1 or 2 variables, see Details
isotropy:character string; specifies the type of isotropy of the corresponding covariance model, see Details
operator:logical; specifies whether the underlying covariance model is an operator, see Details
monotone:character string; specifies the kind of monotonicity of the model
finiterange:logical; specifies whether the underlying covariance model has finite range, see Details
simpleArguments:logical. If TRUE than all the
parameters are real valued (or integer valued).
maxdim:numeric; the maximal dimension, in which the corresponding model is a valid covariance model, see Details
vdim:numeric; dimension of the value of the random field at a single fixed location, equals 1 in most cases, see Details
Class function, directly.
signature(x = CLASS_CLIST): returns the structure
of x
signature(x = CLASS_CLIST): identical with
show-method
signature(x = CLASS_RM): enables accessing
the slots via the "["-operator, e.g. x["maxdim"]
signature(x = CLASS_RM): enables replacing
the slots via the "["-operator
type:can be one of the following strings:
'tail correlation function':indicates that the function returns a tail correlation function (a subclass of the set of positive definite functions)
'positive definite':indicates that the function returns a covariance function (positive definite function)
'negative definite':indicates that the function returns a variogram model (negative definite function)
'process':functions of that type determine the class of processes to be simulated
'method for Gauss processes':methods to simulate Gaussian random fields
'method for Brown-Resnick processes':methods to simulate Brown-Resnick fields
'point-shape function':functions of that type determine the distribution of points in space
'distribution family':e.g. (multivariate) uniform distribution, normal distribution, etc., defined in RandomFields. See RR for a complete list.
'shape function':functions used in, e.g., M3 processes (RPsmith)
'trend':RMtrend or a mixed model
'interface':indicates internal models which are usually
not visible for the users. These functions are the internal
representations of RFsimulate,
RFcov, etc. See RF for a complete list.
'undefined':some models can take different types, depending on the parameter values and/or the submodels
'other type':very very special internal functions, not belonging to any of the above types.
domain:can be one of the following strings:
'single variable':Function depending on a single variable
'kernel':model refers to a kernel, e.g. a non-stationary covariance function
'framework dependent':domain depends on the calling model
'mismatch':this option is used only internally and should never appear
isotropy:can be one of the following strings:
'isotropic':indicates that the model is isotropic
'space-isotropic':indicates that the spatial part of a spatio-temporal model is isotropic
'zero-space-isotropic':this property refers to space-time models; the model is called zerospaceisotropic if it is isotropic as soon as the time-component is zero
'vector-isotropic':multivariate vector model (flow fields) have a different notion of isotropy
'symmetric':the most basic property of any covariance function or variogram model
'cartesian system', 'earth system',
'spherical system', 'cylinder system':different coordinate systems
'non-dimension-reducing':the property f(x) = f(-x)^\top does not hold
'parameter dependent':indicates that the type of isotropy of the model depends on the parameters passed to the model; in particular parameters may be submodels if an operator model is considered
'<mismatch>':this option is used only internally and should never appear
operator:if TRUE, the model requires at least
one submodel
monotone:'mismatch in monotonicity':used if a statement on
the monotonocity does not make sense, e.g. for
RRmodels
'submodel dependent monotonicity':only for operators,
e.g. RMS
'previous model dependent monotonicity':internal; should not be used
'parameter dependent monotonicity':some models change their properties according to the parameters
'not monotone':none of the above categories; either the function is not monotone or properties are unknown
'monotone':isotone or antitone
'Gneiting-Schaback class':function belonging to Euclid's hat in Gneiting's 1999 paper
'normal mixture':scale mixture of the Gaussian model
'completely monotone':completely monotone function
'Bernstein':Bernstein function
Note that
'not monotone' includes 'monotone'
and 'Bernstein'
'monotone' includes 'Gneiting-Schaback class'
'Gneiting-Schaback class' includes 'normal mixture'
'normal mixture' includes 'completely monotone'
finiterange:if TRUE, the covariance of the
model has finite range
maxdim:if a positive integer, maxdim gives the
maximum dimension in which the model is a valid covariance model,
can be Inf;
maxdim=-1 means that the actual maxdim depends on the
parameters; maxdim=-2 means that the actual maxdim depends on
the submodel(s)
vdim:if a positive integer, vdim gives the
dimension of the random field, i.e. univariate, bi-variate, ...;
vdim=-1 means that the actual vdim depends on the
parameters; vdim=-2 means that the actual vdim depends on
the submodel(s)
Alexander Malinowski, Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
Gneiting, T. (1999) Radial positive definite functions generated by Euclid's hat, J. Multivariate Anal., 69, 88-119.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again RFgetModelNames()
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