Running 'perm.coin.check.R' [2s]
  Running 'precision.problem.R' [155s]
  Running 'wilcoxon.kruskal.trend.R' [2s]
Running the tests in 'tests/precision.problem.R' failed.
Complete output:
  > ## This is a hard two sample precision problem.
  > ## What makes it hard is that the sum of the 
  > ## first 2 values of y are the same as the sum
  > ## of the second two, and to get the correct 
  > ## answer you need to get them exactly equal
  > ## You should get the same answer regardless of 
  > ## whether you multiply y by a constant
  > ## Here both coin 1.0-8 and perm 0.9.1 give the correct answer
  > ## (earlier versions of coin had problems with this example)
  > library(coin)
  Loading required package: survival
  > packageDescription("coin")$Version
  [1] "1.4-3"
  > library(perm)
  > y<-c(1.11,2.22,3.33,0,100,1)
  > g<-as.factor(c(1,1,0,0,1,0))
  > independence_test(y~g,distribution=exact())
  
  	Exact General Independence Test
  
  data:  y by g (0, 1)
  Z = -1.005, p-value = 0.5
  alternative hypothesis: two.sided
  
  > permTS(y~g,method="exact.ce",alternative="two.sided",control=permControl(tsmethod="abs"))
  
  	Exact Permutation Test (complete enumeration)
  
  data:  y by g
  p-value = 0.5
  alternative hypothesis: true mean g=0 - mean g=1 is  0
  sample estimates:
  mean g=0 - mean g=1 
                  -33 
  
  > independence_test(y~g,distribution=exact(),alternative="less")
  
  	Exact General Independence Test
  
  data:  y by g (0, 1)
  Z = -1.005, p-value = 0.25
  alternative hypothesis: less
  
  > permTS(y~g,method="exact.ce",alternative="less")
  
  	Exact Permutation Test (complete enumeration)
  
  data:  y by g
  p-value = 0.25
  alternative hypothesis: true mean g=0 - mean g=1 is less than 0
  sample estimates:
  mean g=0 - mean g=1 
                  -33 
  
  > independence_test(y~g,distribution=exact(),alternative="greater")
  
  	Exact General Independence Test
  
  data:  y by g (0, 1)
  Z = -1.005, p-value = 0.85
  alternative hypothesis: greater
  
  > permTS(y~g,method="exact.ce",alternative="greater")
  
  	Exact Permutation Test (complete enumeration)
  
  data:  y by g
  p-value = 0.85
  alternative hypothesis: true mean g=0 - mean g=1 is greater than 0
  sample estimates:
  mean g=0 - mean g=1 
                  -33 
  
  > 
  > y<-4.44*y
  > independence_test(y~g,distribution=exact())
  
  	Exact General Independence Test
  
  data:  y by g (0, 1)
  Z = -1.005, p-value = 0.5
  alternative hypothesis: two.sided
  
  > permTS(y~g,method="exact.ce",alternative="two.sided",control=permControl(tsmethod="abs"))
  
  	Exact Permutation Test (complete enumeration)
  
  data:  y by g
  p-value = 0.5
  alternative hypothesis: true mean g=0 - mean g=1 is  0
  sample estimates:
  mean g=0 - mean g=1 
              -146.52 
  
  > 
  > proc.time()
     user  system elapsed 
     2.04    0.31    2.37