Scale model for arbitrary areas of scales
Let s_x the scaling at location x and p a bijective penalizing function for (different) scales. Then covariance function is given by
C(x,y) = φ(\|x-y\| + |p(s_x) - p(s_y)|)
RMscale(phi, scaling, penalty, var, scale, Aniso, proj)
phi |
isotropic submodel |
scaling |
model that gives the non-stationary scaling s_x |
penalty |
bijective function p applied to the |
var,scale,Aniso,proj |
optional arguments; same meaning for any
|
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
Bonat, W.H. , Ribeiro, P. Jr. and Schlather, M. (2019) Modelling non-stationarity in scale. In preparation.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
x <- seq(0,1, 0.01)
scale <- RMcovariate(x=c(0,1), y=c(1,0),#2 areas separated by the 1st bisector
grid=FALSE, data=c(1, 3))
model <- RMscale(RMexp(), scaling = scale, penalty=RMid() / 2)
plot(z <- RFsimulate(model, x, x))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.