Bivariate Delay Effect
RMdelay is a (m+1)-variate stationary covariance model.
which depends on a univariate stationary covariance model C_0.
The corresponding covariance function only depends on the difference h between two points in d-dimensional space and is given by
C(h)=(C_0(h - s_i +s_j))_{i,j=0,…,m}
where h \in R^{d x m} and s_0=0
RMdelay(phi,s,var, scale, Aniso, proj)
phi |
a univariate stationary covariance model, that means an
|
s |
a d x m-dimensional shift matrix, where d is the dimension of the space, giving the components s=(s_1,..., s_m) where the s_i are vectors. |
var,scale,Aniso,proj |
optional arguments; same meaning for any
|
Here, a multivariate random field is obtained from a single univariate random field by shifting it by a fixed value.
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
Schlather, M., Malinowski, A., Menck, P.J., Oesting, M. and Strokorb, K. (2015) Analysis, simulation and prediction of multivariate random fields with package RandomFields. Journal of Statistical Software, 63 (8), 1-25, url = ‘http://www.jstatsoft.org/v63/i08/’
Wackernagel, H. (2003) Multivariate Geostatistics. Berlin: Springer, 3nd edition.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again x <- y <- seq(-10,10,0.2) model <- RMdelay(RMstable(alpha=1.9, scale=2), s=c(4,4)) plot(model, dim=2, xlim=c(-6, 6), ylim=c(-6,6)) simu <- RFsimulate(model, x, y) plot(simu, zlim="joint")
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