https://github.com/cran/RandomFields
Tip revision: 6eca414de4c835af2032db4cae6c05e9cc684529 authored by Martin Schlather on 23 April 2016, 15:04:07 UTC
version 3.1.11
version 3.1.11
Tip revision: 6eca414
RMcovariate.Rd
\name{RMcovariate}
\alias{RMcovariate}
\title{Model for covariates}
\description{
The model makes covariates available.
}
\usage{
RMcovariate(c, x, y=NULL, z=NULL, T=NULL, grid, var, scale,
Aniso, proj, raw, norm, addNA)
}
\arguments{
\item{scale, Aniso, proj, var}{optional arguments; same meaning for any
\command{\link{RMmodel}}. If not passed, the above
covariance function remains unmodified.}
\item{c}{vector or matrix of data
}
\item{x,y,z,T,grid}{optional.
The usual arguments as in \command{\link{RFsimulate}} to define the
locations where the covariates are given
}
% \item{factor}{vector or matrix of numerical values.
% The length of the vector must match the given number of locations.
% }
%
% \item{var}{variance, i.e. factor multiplied to the data, which can be
% estimated through ML
% }
\item{raw}{
logical. If \code{FALSE} then the data are interpolated. This
approach is always save, but might be slow.
If \code{TRUE} then the data may be accessed when covariance
matrices are calculated. No rescaling or anisotropy definition
is allowed in combination with the model. The use is dangerous,
but fast.
Default: FALSE
}
\item{norm}{optional model that gives the norm between locations}
\item{addNA}{
If \code{addNA} is \code{TRUE}, then an additional
(linear) factor is estimated in an estimation framework.
This parameter must be set in particular when \command{RMcovariate}
passes several covariates.
}
}
\note{
\itemize{
\item \code{c}, \code{x},
also accept lists of data. However, its use is not in an advanced
stage yet.
}
}
\details{
The functions interpolates (nearest neighbour) between the values.
}
\value{
\command{\link{RMcovariate}} returns an object of class \code{\link[=RMmodel-class]{RMmodel}}
}
\author{Martin Schlather, \email{schlather@math.uni-mannheim.de}
}
\seealso{
\command{\link{RMfixcov}},
\command{\link{RMmodel}},
\command{\link{RMtrend}}
}
\examples{
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
z <- 0.2 + (1:10)
RFfctn(RMcovariate(z), 1:10)
RFfctn(RMcovariate(z, 1:10), c(2, 2.1, 2.5, 3))
\dontshow{FinalizeExample()}
}
\keyword{spatial}
\keyword{models}