checkRF {CoSMoS} | R Documentation |
Numerical and visual check of generated random fields
Description
Compares generated random fields sample statistics with the theoretically
expected values (similar to checkTS
). It also returns graphical output for
visual check.
Usage
checkRF(RF, lags = 30, nfields = 49, method = "stat")
Arguments
RF |
output of |
lags |
number of lags of empirical STCF to be considered in the graphical output (default set to 30) |
nfields |
number of fields to be used in the numerical and graphical output (default set to 49). As the plots are arranged in a matrix with nrows as close as possible to ncol, we suggest using values such as 3x3, 3x4, 7x8, etc. |
method |
report method - |
Examples
## The example below refers to the fitting and simulation of 10 random fields
## of size 10x10 with AR(1) temporal correlation. As the fitting algorithm has
## O((mxm)^3) complexity for a mxm field, this setting allows for quick fitting
## and simulation (short CPU time). However, for a more effective visualization
## and reliable performance assessment, we suggest to generate a larger number
## of fields (e.g. 100 or more) of size about 30X30. This setting needs more
## CPU time but enables more effective comparison of theoretical and
## empirical statistics. Sizes larger than about 50x50 can be unpractical
## on standard machines.
fit <- fitVAR(
spacepoints = 10,
p = 1,
margdist ='burrXII',
margarg = list(scale = 3, shape1 = .9, shape2 = .2),
p0 = 0.8,
stcsid = "clayton",
stcsarg = list(scfid = "weibull", tcfid = "weibull",
copulaarg = 2,
scfarg = list(scale = 20, shape = 0.7),
tcfarg = list(scale = 1.1, shape = 0.8))
)
sim <- generateRF(n = 12,
STmodel = fit)
checkRF(RF = sim,
lags = 10,
nfields = 12)