Running examples in ‘CompRandFld-Ex.R’ failed
The error most likely occurred in:

> ### Name: Covariogram
> ### Title: Computes covariance, variogram and extremal coefficient
> ###   functions
> ### Aliases: Covariogram
> ### Keywords: Composite
> 
> ### ** Examples
> 
> library(CompRandFld)
> library(RandomFields)
Loading required package: sp
Loading required package: RandomFieldsUtils
Consider the use of one of 
	RFoptions(install.control=list(force=FALSE))
	RFoptions(install.control=list(repos=NULL))
	RFoptions(install.control=NULL)
If you use it, the package might run faster the next time it is loaded.
Recompilation is at your own risk. There is currently no guarantee that it will work.
In case of problems:  Please contact the maintainer martin.schlather@math.uni-mannheim.de.


Attaching package: ‘RandomFields’

The following objects are masked from ‘package:RandomFieldsUtils’:

    RFoptions, checkExamples

> library(scatterplot3d)
> set.seed(31231)
> 
> # Set the coordinates of the points:
> x <- runif(100, 0, 10)
> y <- runif(100, 0, 10)
> coords<-cbind(x,y)
> 
> ################################################################
> ###
> ### Example 1. Plot of covariance and variogram functions
> ### estimated from a Gaussian random field with exponent 
> ### correlation. One spatial replication is simulated.
> ###
> ###
> ###############################################################
> 
> # Set the model's parameters:
> corrmodel <- "exponential"
> mean <- 0
> sill <- 1
> nugget <- 0
> scale <- 2
> 
> # Simulation of the Gaussian random field:
> data <- RFsim(coordx=coords, corrmodel=corrmodel, param=list(mean=mean,
+               sill=sill, nugget=nugget, scale=scale))$data
> 
> # Maximum composite-likelihood fitting of the Gaussian random field:
> 
> start<-list(scale=scale,sill=sill,mean=mean(data))
> fixed<-list(nugget=nugget)
> # Maximum composite-likelihood fitting of the random field:
> fit <- FitComposite(data, coordx=coords, corrmodel=corrmodel,likelihood="Marginal",
+                      type="Pairwise",start=start,fixed=fixed,maxdist=6)
> 
> # Results:
> print(fit)

##################################################################
Maximum Composite-Likelihood Fitting of Gaussian Random Fields

Setting: Marginal Composite-Likelihood 

Model associated to the likelihood objects: Gaussian 

Type of the likelihood objects: Pairwise 

Covariance model: exponential 
Number of spatial coordinates: 100 
Number of dependent temporal realisations: 1 
Number of replicates of the random field: 1 
Number of estimated parameters: 3 

Maximum log-Composite-Likelihood value: -6734.94

Estimated parameters:
   mean    scale     sill  
-0.2512   1.1151   0.5963  

##################################################################
> 
> # Empirical estimation of the variogram:
> vario <- EVariogram(data, x, y)
> 
> # Plot of covariance and variogram functions:
> par(mfrow=c(1,2))
> Covariogram(fit, show.cov=TRUE, show.range=TRUE,
+             show.vario=TRUE, vario=vario,pch=20)
> 
> 
> ################################################################
> ##
> ### Example 2. Plot of covariance and extremal coefficient
> ### functions estimated from a max-stable random field with
> ### exponential correlation. n idd spatial replications are
> ### simulated.
> ###
> ###############################################################
> 
> set.seed(1156)
> # Simulation of the max-stable random field:
> data <- RFsim(coordx=coords, corrmodel=corrmodel, model="ExtGauss", replicates=20,
+               param=list(mean=mean,sill=sill,nugget=nugget,scale=scale))$data
Warning in RandomFields::MaxStableRF(x = initparam$coordx, y = initparam$coordy,  :
  The function is obsolete. Use 'RFsimulate' instead.
R: malloc.c:2539: sysmalloc: Assertion `(old_top == initial_top (av) && old_size == 0) || ((unsigned long) (old_size) >= MINSIZE && prev_inuse (old_top) && ((unsigned long) old_end & (pagesize - 1)) == 0)' failed.