RMmodelgenerator-class: Class 'RMmodelgenerator'

Description Creating Objects Slots Extends Methods Details Author(s) References See Also Examples

Description

Class for all functions of this package with prefix RM, i.e. all functions that generate objects of class RMmodel; direct extension of class function.

Creating Objects

Objects should not be created by the user!

Slots

.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

Extends

Class function, directly.

Methods

show

signature(x = CLASS_CLIST): returns the structure of x

print

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

Details

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)

Author(s)

Alexander Malinowski, \martin

References

See Also

RMmodel, RFgetModelNames

Examples

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RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again
RFgetModelNames()

RandomFields documentation built on Jan. 19, 2022, 1:06 a.m.