Running examples in 'DiceOptim-Ex.R' failed
The error most likely occurred in:

> ### Name: noisy.optimizer
> ### Title: Optimization of homogenously noisy functions based on Kriging
> ### Aliases: noisy.optimizer
> 
> ### ** Examples
> 
> 
> ##########################################################################
> ### EXAMPLE 1: 3 OPTIMIZATION STEPS USING EQI WITH KNOWN NOISE         ###
> ### AND KNOWN COVARIANCE PARAMETERS FOR THE BRANIN FUNCTION            ###
> ##########################################################################
> 
> set.seed(10)
> library(DiceDesign)
> # Set test problem parameters
> doe.size <- 9
> dim <- 2
> test.function <- get("branin2")
> lower <- rep(0,1,dim)
> upper <- rep(1,1,dim)
> noise.var <- 0.1
> 
> # Build noisy simulator
> funnoise <- function(x)
+ {     f.new <- test.function(x) + sqrt(noise.var)*rnorm(n=1)
+       return(f.new)}
> 
> # Generate DOE and response
> doe <- as.data.frame(lhsDesign(doe.size, dim)$design)
> y.tilde <- funnoise(doe)
> 
> # Create kriging model
> model <- km(y~1, design=doe, response=data.frame(y=y.tilde),
+      covtype="gauss", noise.var=rep(noise.var,1,doe.size), 
+      lower=rep(.1,dim), upper=rep(1,dim), control=list(trace=FALSE))
> 
> # Optimisation with noisy.optimizer (n.ite can be increased)
> n.ite <- 2 
> optim.param <- list()
> optim.param$quantile <- .9
> optim.result <- noisy.optimizer(optim.crit="EQI", optim.param=optim.param, model=model,
+ 		n.ite=n.ite, noise.var=noise.var, funnoise=funnoise, lower=lower, upper=upper,
+ 		NoiseReEstimate=FALSE, CovReEstimate=FALSE)
Starting noisy optimization with the following criterion and parameters 

EQI

0.9FALSE
----------------- 



Tue Jul 07 19:48:39 2020
Domains:
 0.000000e+00   <=  X1   <=    1.000000e+00 
 0.000000e+00   <=  X2   <=    1.000000e+00 

Data Type: Floating Point
Operators (code number, name, population) 
	(1) Cloning........................... 	2
	(2) Uniform Mutation.................. 	1
	(3) Boundary Mutation................. 	1
	(4) Non-Uniform Mutation.............. 	1
	(5) Polytope Crossover................ 	1
	(6) Simple Crossover.................. 	2
	(7) Whole Non-Uniform Mutation........ 	1
	(8) Heuristic Crossover............... 	2
	(9) Local-Minimum Crossover........... 	0

HARD Maximum Number of Generations: 12
Maximum Nonchanging Generations: 2
Population size       : 12
Convergence Tolerance: 1.000000e-21

Using the BFGS Derivative Based Optimizer on the Best Individual Each Generation.
Not Checking Gradients before Stopping.
Not Using Out of Bounds Individuals and Not Allowing Trespassing.

Maximization Problem.


Generation#	    Solution Value

      0 	1.139212e-01
      2 	1.187577e-01
      3 	2.969090e-01
      4 	2.969090e-01
      5 	2.969090e-01
      7 	2.969090e-01
      9 	2.969090e-01

'wait.generations' limit reached.
No significant improvement in 2 generations.

Solution Fitness Value: 2.969090e-01

Parameters at the Solution (parameter, gradient):

 X[ 1] :	9.488739e-01	G[ 1] :	-1.379394e-09
 X[ 2] :	0.000000e+00	G[ 2] :	-5.671372e-01

Solution Found Generation 9
Number of Generations Run 12

Tue Jul 07 19:48:40 2020
Total run time : 0 hours 0 minutes and 1 seconds
Creating obs:0.9488738912525190

Error in validObject(covStruct) : 
  invalid class "covTensorProduct" object: The range parameters must have positive values
Error occured during hyperparameter reestimation - old hyperparameter values used instead
Error in validObject(covStruct) : 
  invalid class "covTensorProduct" object: The range parameters must have positive values
Calls: noisy.optimizer ... .local -> update.km -> km -> covStruct.create -> validObject
Execution halted