\name{RMfixcov} \alias{RMfixcov} \title{Fixed Covariance Matrix} \description{ \command{\link{RMfixcov}} is a user-defined covariance according to the given covariance matrix. It extends to the space through a Voronoi tessellation. } \usage{ RMfixcov(M, x, y=NULL, z=NULL, T=NULL, grid, var, proj, raw, norm) } \arguments{ \item{M}{a numerical matrix defining the user-defined covariance for a random field; the matrix should be positive definite, symmetric and its dimension should be equal to the length of observation or simulation vector.} \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{var,proj}{optional arguments; same meaning for any \command{\link{RMmodel}}. If not passed, the above covariance function remains unmodified.} \item{raw}{\argRaw} \item{norm}{\argNorm} % \item{vdim}{an integer value; defining the response dimension.} } \note{ Starting with version 3.0.64, the former argument \code{element} is replaced by the \code{general} option \code{set} in \command{\link{RFoptions}}. } \details{ The covariances passed are implemented for the given locations. Within any Voronoi cell (around a given location) the correlation is assumed to be one. In particular, it is used in \command{\link{RFfit}} to define neighbour or network structure in the data. } \value{ \command{\link{RMfixcov}} returns an object of class \code{\link[=RMmodel-class]{RMmodel}}. } \references{ \itemize{ \item Ober, U., Ayroles, J.F., Stone, E.A., Richards, S., Zhu, D., Gibbs, R.A., Stricker, C., Gianola, D., Schlather, M., Mackay, T.F.C., Simianer, H. (2012): \emph{Using Whole Genome Sequence Data to Predict Quantitative Trait Phenotypes in Drosophila melanogaster}. PLoS Genet 8(5): e1002685. } } \me \seealso{ \command{\link{RMcovariate}}, \command{\link{RMmodel}}, \command{\link{RFsimulate}}, \command{\link{RFfit}}, \command{\link{RMuser}}. } \keyword{spatial} \keyword{models} \examples{\dontshow{StartExample(reduce=FALSE)} RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again ## Example 1 showing that the covariance structure is correctly implemented n <- 10 C <- matrix(runif(n^2), nc=n) (C <- C \%*\% t(C)) RFcovmatrix(RMfixcov(C), 1:n) ## Example 2 showing that the covariance structure is interpolated RFcovmatrix(RMfixcov(C, 1:n), c(2, 2.1, 2.5, 3)) ## Example 3 showing the use in a separable space-time model model <- RMfixcov(C, 1:n, proj="space") * RMexp(s=40, proj="time") (z <- RFsimulate(model, x = seq(0,12, 0.5), T=1:100)) plot(z) \dontshow{FinalizeExample()}}