Documentation of major changings
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
RFfitruns much faster now
modus operandichanged for estimating
Corrections done in 3.0.56 (Jan 2015)
log Gauss field corrected (has been a log log Gauss field)
RMconstantis now called
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)
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.
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
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
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 arguments are kept in the functions that are considered as being absolutely necessary. All the other arguments can be included as options.
RFguiis an instructive interface based on tcl/tk, replacing the former
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 arguments 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.
RFratiotesthas been added.
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.
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.
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