R: Documentation of major changings

Major Revisions {RandomFields} | R Documentation

## Documentation of major changings

### 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

    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

[Package RandomFields version 3.1.50 Index]