* using log directory 'd:/Rcompile/CRANpkg/local/2.8/ROptEst.Rcheck'
* using R version 2.8.0 (2008-10-20)
* using session charset: ISO8859-1
* checking for file 'ROptEst/DESCRIPTION' ... OK
* this is package 'ROptEst' version '0.6.0'
* checking package name space information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking whether package 'ROptEst' can be installed ... OK
* checking package directory ... OK
* checking for portable file names ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the name space can be loaded with stated dependencies ... OK
* checking for unstated dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* creating ROptEst-Ex.R ... OK
* checking examples ... ERROR
Running examples in 'ROptEst-Ex.R' failed.
The error most likely occurred in:

> ### * roptest
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: roptest
> ### Title: Optimally robust estimation
> ### Aliases: roptest
> ### Keywords: robust
> 
> ### ** Examples
> 
> #############################
> ## 1. Binomial data
> #############################
> ## generate a sample of contaminated data
> ind <- rbinom(100, size=1, prob=0.05) 
> x <- rbinom(100, size=25, prob=(1-ind)*0.25 + ind*0.9)
> 
> ## ML-estimate
> MLEstimator(x, BinomFamily(size = 25))
Evaluations of Maximum likelihood estimate:
-------------------------------------------
An object of class "Estimate" 
generated by call
  MLEstimator(x = x, ParamFamily = BinomFamily(size = 25))
samplesize:   100
estimate:
      prob    
  0.268400000 
 (0.008862538)
fixed part of the parameter:
size 
  25 
asymptotic (co)variance (multiplied with samplesize):
[1] 0.007854458
Criterium:
negative log-likelihood 
               253.0469 
> 
> ## compute optimally robust estimator (known contamination)
> roptest(x, BinomFamily(size = 25), eps = 0.05, steps = 3)
maximum iterations reached!
 achieved precision:	 0.01650714 
maximum iterations reached!
 achieved precision:	 0.06620516 
maximum iterations reached!
 achieved precision:	 0.04311427 
Evaluations of 3-step estimate:
-------------------------------
An object of class "Estimate" 
generated by call
  roptest(x = x, L2Fam = BinomFamily(size = 25), eps = 0.05, steps = 3)
samplesize:   100
estimate:
      prob    
  0.256472818 
 (0.009379927)
asymptotic (co)variance (multiplied with samplesize):
[1] 0.008798302
Infos:
     method    message                                                  
[1,] "roptest" "3-step estimate for Binomial family"                    
[2,] "roptest" "computation of IC, asvar and asbias via useLast = FALSE"
asymptotic bias:
[1] 0.06195664
(partial) influence curve:
An object of class "ContIC" 
### name:	 IC of contamination type 

### L2-differentiable parametric family:	 Binomial family 
### param:	An object of class "ParamFamParameter"
name:	probability of success
prob:	0.256489349454423
fixed part of param.:
	size:	25
trafo:
     prob
prob    1

### neighborhood radius:	 0.5 

### clip:	[1] 0.1239133
### cent:	[1] -0.003693803
### stand:
           prob
prob 0.01251778

### Infos:
     method  message                          
[1,] "optIC" "optimally robust IC for 'asMSE'"
steps:
[1] 3
> 
> ## compute optimally robust estimator (unknown contamination)
> roptest(x, BinomFamily(size = 25), eps.lower = 0, eps.upper = 0.1, steps = 3)
maximum iterations reached!
 achieved precision:	 0.006604717 
maximum iterations reached!
 achieved precision:	 0.04409352 
Error in uniroot(getIneffDiff, lower = lower, upper = upper, tol = .Machine$double.eps^0.25,  : 
  f() values at end points not of opposite sign
Calls: roptest ... radiusMinimaxIC -> radiusMinimaxIC -> .local -> uniroot
Execution halted