| TIC {SpatialExtremes} | R Documentation |
Computes a "generalization" of the Takeuchi's information criterion when the model is miss-specified.
TIC(object, ...)
object |
An object of class maxstab. Often, it will be the
output of function fitmaxstab |
... |
Additional objects of class maxstab for which TIC
should be computed. |
TIC is like AIC so that when comparing models one wants to get the lowest TIC score.
Numeric.
Mathieu Ribatet
Varin, C. and Vidoni, P. (2005) A note on composite likelihood inference and model selection. Biometrika 92(3):519–528.
require(RandomFields)
##Define the coordinate of each location
n.site <- 50
locations <- matrix(runif(2*n.site, 0, 100), ncol = 2)
colnames(locations) <- c("lon", "lat")
##Simulate a max-stable process - with unit Frechet margins
ms0 <- MaxStableRF(locations[,1], locations[,2], grid=FALSE, model="stable",
param=c(0,1,.2,30, .5), maxstable="extr",
n = 40)
ms0 <- t(ms0)
M0 <- fitmaxstab(ms0, locations, "powexp", std.err.type = "score",
fit.marge = FALSE)
M1 <- fitmaxstab(ms0, locations, "cauchy", std.err.type = "score",
fit.marge = FALSE)
TIC(M0, M1)