RandomFields (version 3.0.5)

RandomFields-package: Simulation and Analysis of Random Fields

Description

This version 3 is a major revision of version 2 with many important changings, see section Major Revision below.

The package RandomFields offers various tools for

1. simulation

of different kinds of random fields, including

• multivariate, spatial, spatio-temporal Gaussian random fields,
• Poisson fields, binary fields, Chi2 fields and
• max-stable fields.

It can also deal with non-stationarity and anisotropy of these processes and conditional simulation (for Gaussian random fields, currently).

model estimation for regionalizd variables and data analysis, using different LSQ and MLE procedures (currently for Gaussian random fields only) model estimation for (geostatistical) linear (mixed) models

Major Revision: changings

The following major changings took place with respect to version 2:

• S4 objects
  • RandomFieldsis now based on S4 objects using the packagesp. The functions accept bothspobjects and simple objects as used in version 2.
  • The functions return S4 objects ifspConform=TRUE, otherwise simple objects as in version 2.
  • plotandprintrecognise these S4 objects
• Documentation
  • each model has now its own man page;
  • classes of models and functions are bundled in several pages: Covariance models start withRM, distribution families withRR, processes withRP, user functions withRF
  • the man pages of several functions are split into two parts: (i) a beginners man page which includes a link to (ii) man pages for advanced users
• Interfaces
  • The interfaces become simpler, at the same time more powerful then the functions in version 2. E.g.,RFsimulatecan perform unconditional simulation, conditional simulation and random imputing.
  • Only those parameters are kept in the functions that are considered as being absolutely necessary. All the other parameters can be included asoptions.
  • RFguiis an instructive interface based on tcl/tk, replacing the formerShowModels
• Inference for Gaussian random fields
  • RFfithas undergone a major revision. E.g.: (i) estimation random effects model with spatial covariance structure

    (ii) automatic estimation of 10 and more parameters in multivariate and/or space-time models

  • RFempiricalvariogramis now based on an fft algorithm if the data are on a grid, even allowing for missing values.
• Processes
  • Maxstable processes
  modelling ofmaxstable processeshas been enhanced, including (i) the simulation of Brown-Resnick processes (ii) initial support oftail correlation functions;
• Further processes

chi2 processes, compound Poisson processes, binary processes added.