Non-Separable Space-Time model
RMnsst is a univariate stationary spaceisotropic covariance model
whose corresponding covariance is given by
C(h,u)= (ψ(u)+1)^{-δ/2} φ(h /√(ψ(u) +1))
RMnsst(phi, psi, delta, var, scale, Aniso, proj)
phi |
is a normal mixture |
psi |
is a variogram |
delta |
a numerical value; must be greater than or equal to the spatial dimension of the field. |
var,scale,Aniso,proj |
optional arguments; same meaning for any
|
This model is used for space-time modelling where the spatial component is isotropic.
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
Gneiting, T. (1997) Normal scale mixtures and dual probability densitites, J. Stat. Comput. Simul. 59, 375-384.
Gneiting, T. (2002) Nonseparable, stationary covariance functions for space-time data, JASA 97, 590-600.
Gneiting, T. and Schlather, M. (2001) Space-time covariance models. In El-Shaarawi, A.H. and Piegorsch, W.W.: The Encyclopedia of Environmetrics. Chichester: Wiley.
Schlather, M. (2010) On some covariance models based on normal scale mixtures. Bernoulli, 16, 780-797.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again model <- RMnsst(phi=RMgauss(), psi=RMfbm(alpha=1), delta=2) x <- seq(0, 10, 0.25) plot(model, dim=2) plot(RFsimulate(model, x=x, y=x))
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