Documentation of major changings

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Description

This man pages documents some major changings in RandomFields.

Changes done in 3.1.0 (Summer 2015)

  • full (univariate) trend modelling

  • error in particular in RFfit corrected

  • RFfit runs much faster now

  • effects of modus operandi changed for estimating

Corrections done in 3.0.56 (Jan 2015)

  • log Gauss field corrected (has been a log log Gauss field)

  • RMconstant is now called RMfixcov

Corrections done in 3.0.55 (Jan 2015)

  • Conditional simulation: several severe typos corrected.

Major Revision: changings from Version 2 to Version 3 (Jan 2014)

  • S4 objects

    • RandomFields is now based on S4 objects using the package sp. The functions accept both sp objects and simple objects as used in version 2. See also above.

  • Documentation

    • each model has now its own man page;

    • classes of models and functions are bundled in several pages: Covariance models start with RM, distribution families with RR, processes with RP, user functions with RF

    • 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., RFsimulate can perform unconditional simulation, conditional simulation and random imputing.

    • Only those arguments are kept in the functions that are considered as being absolutely necessary. All the other arguments can be included as options.

    • RFgui is an instructive interface based on tcl/tk, replacing the former ShowModels

  • Inference for Gaussian random fields

    • RFfit has undergone a major revision. E.g.:

      (i) estimation random effects model with spatial covariance structure

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

    • RFempiricalvariogram is now based on an fft algorithm if the data are on a grid, even allowing for missing values.

    • RFratiotest has been added.

  • Processes

    • Maxstable processes modelling of maxstable processes has been enhanced, including

      (i) the simulation of Brown-Resnick processes

      (ii) initial support of tail correlation functions;

    • Further processes chi2 processes, compound Poisson processes, binary processes added.

  • Models

    • the formula notation for linear models may now be defined

    • Novel, user friendly definition of the covariance models

    • Multivariate and vector valued random fields are now fully included

    • The user may now define his own functions, to some extend.

    • The trend allows for much more flexibility

    • Distributions may now included which will be extended to Bayesian modelling in future.

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

## S4 vs S3
x <- seq(0, 10, 0.1)
model <- RMexp()
plot(RFsimulate(model, x)) ## S4
plot(RFsimulate(model, x, spConform=FALSE)) ## no class

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