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

Attaching package: 'RandomFields'

The following object is masked from 'package:RandomFieldsUtils':

    RFoptions

The following objects are masked from 'package:base':

    abs, acosh, asin, asinh, atan, atan2, atanh, cos, cosh, exp, expm1,
    floor, gamma, lgamma, log, log1p, log2, logb, max, min, round, sin,
    sinh, sqrt, tan, tanh, trunc

> 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