RandomFields {RandomFields} | R Documentation |
The package RandomFields
allows for simulating various kinds
of random fields, including anisotropic
processes. Furthermore, algorithms for
conditional simulation and simulation of
max-stable random fields are provided.
Additionally, the package includes tools for analysing spatial data: Hurst parameter, fractal dimension, empirical variogram, interactive fitting of parameters, LSQ and MLE estimation of parameters. Basic kriging procedures are also provided.
Further extensions of the package are planned.
The following random fields and related functionalities are provided by the package.
CondSimu
: conditional simulation
CovarianceFct
: covariance functions or
variogram models
EmpiricalVariogram
: empirical variogram
GaussRF
: simulation of Gaussian random
fields; nice examples to get familiar with the
simulation features of the package
Kriging
: simple and ordinary kriging
mleRF
: maximum likelihood estimator and lsq for
random field parameters
PrintMethodList
: list of implemented
simulation methods
ShowModels
: interactive, graphical choice of
models
soil
: Soil physical and chemical data;
the example
gives a simple geostatistical analysis using
features of the package
CovarianceFct
: covariance models for
extremal Gaussian random fields
MaxStableRF
: simulation of max-stable
random fields
Functions used in diverse simulation methods:
DeleteRegister
: deleting internal registers
RFparameters
: control parameters (advanced settings)
Functions of general purpose:
eval.parameters
: provides an interactive menu
fractal.dim
: estimation of the fractal dimension
hurst
: estimation of the Hurst parameter
regression
: interactive regression plot
Many thanks to Martin Maechler, Paulo Ribeiro, and Tilmann Gneiting for proof-reading parts of the code and the help text for V1.0 of this package.
The coding of V1.0 has been supported by the EU TMR network ERB-FMRX-CT96-0095 on ``Computational and statistical methods for the analysis of spatial data'' in 1999, and by the German Federal Ministry of Research and Technology (BMFT) grant PT BEO 51-0339476C during 2000-03.
Martin Schlather, martin.schlather@cu.lu http://www.cu.lu/~schlathe
This package is announced in:
Schlather, M. (2001) Simulation of stationary and isotropic random fields. R-News 1 (2), 18-20.
Schlather, M. (2004) Simulation of random fields and applications. In preparation.