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.
Starting with version 2.0, it also allows for the simulation of random fields that are non-stationary or multivariate or sophisticated space-time fields. fitvario allows for multivariate models and mixed effect models.
There are some changings in the definitions and in the output, see help("changings")
The following random fields and related functionalities are provided by the package.
stationary and isotropic Gaussian random fields
CondSimu
: conditional simulation
CovarianceFct
,
sophisticated models: covariance functions and
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
fitvario
: variogram/covariance function fit
by least squares, maximum likelihood and cross validation
techniques
PrintMethodList
: list of implemented
simulation methods
ShowModels
: interactive, graphical choice of
models – currently not available.
Use ShowModels in version 1.3.x
soil
: Soil physical and chemical data;
the example
gives a simple geostatistical analysis using
features of the package
stationary (and isotropic) max-stable random fields
CovarianceFct
: covariance models for
extremal Gaussian random fields
MaxStableRF
: simulation of max-stable
random fields
Note: Simulation algorithm for Brown-Resnick processes will come up soon.
stationary and isotropic Poisson random fields
(not implemented yet)
Data and example code:
soil
: soil physical data
papers
: code used in the papers published by
the author
weather
: UWME weather data
Functions used in diverse simulation methods:
DeleteRegister
: deleting internal registers
RFparameters
: control parameters (advanced settings)
Functions of general purpose:
fractal.dim
: estimation of the fractal dimension
hurst
: estimation of the Hurst parameter
Print
: nice print function
regression
: interactive regression plot
Locator
, Readline
:
locator
and readline
,
respectively, with storage and replay functionality
sleep.milli
: sets the process into sleeping status
In the beta version, the following functionalities are currently not available:
numerical evaluation of the covariance function in tbm2
Harvard Rue's Markov fields
Many thanks to
Peter Menck implemented the multivariate circulant embedding for version 2.0.
Yindeng Jiang jiangyindeng@gmail.com implemented the circulant embedding methods ‘cutoff’ and ‘intrinsic’ in 2004 for the versions 1.2.
Martin Maechler, Paulo Ribeiro, and Tilmann Gneiting were proof-reading parts of the code and the help text for the versions 1.0.
V1.0 has been financially supported by the German Federal Ministry of Research and Technology (BMFT) grant PT BEO 51-0339476C during 2000-03.
V1.0 has been financially supported by the EU TMR network ERB-FMRX-CT96-0095 on “Computational and statistical methods for the analysis of spatial data” in 1999.
Martin Schlather, martin.schlather@math.uni-goettingen.de http://www.stochastik.math.uni-goettingen.de/~schlather;
This package is announced in and can be cited by:
Schlather, M. (2001) Simulation of stationary and isotropic random fields. R-News 1 (2), 18-20.