Running '00-pairedTest.R' [11s]
  Comparing '00-pairedTest.Rout' to '00-pairedTest.Rout.save' ... OK
  Running '01-bankedTest.R' [167s]
  Running '03-betamix.R' [9s]
  Comparing '03-betamix.Rout' to '03-betamix.Rout.save' ... OK
Running the tests in 'tests/01-bankedTest.R' failed.
Complete output:
  > library(NewmanOmics)
  > 
  > data(GSE6631)
  > HN <- as.matrix(log2(1 + GSE6631))
  > HN <- log2((1/19)*median(HN) + HN)
  > 
  > set.seed(12345)
  > picked <- sample(nrow(HN), 2000)
  > bankMatrix <- HN[picked, seq(1, ncol(HN), 2)]
  > testSet <- HN[picked, seq(2, 6, 2)]
  > 
  > bs <- bankStat(testSet = testSet, bankMatrix = bankMatrix)
  > class(bs) # now a list. Should we create a class?
  [1] "list"
  > names(bs) # two entries
  [1] "nu.statistics" "p.values"     
  > summary(bs$nu.statistics)
      Cancer.1            Cancer.2           Cancer.3         
   Min.   :-12.52279   Min.   :-10.7697   Min.   :-11.534449  
   1st Qu.: -0.52482   1st Qu.: -0.5616   1st Qu.: -0.576519  
   Median :  0.29960   Median :  0.2910   Median : -0.077493  
   Mean   :  0.08296   Mean   :  0.1038   Mean   : -0.005766  
   3rd Qu.:  0.99903   3rd Qu.:  0.9687   3rd Qu.:  0.500584  
   Max.   :  5.87033   Max.   :  8.5824   Max.   :  8.547029  
  > summary(bs$p.values)
      Cancer.1         Cancer.2         Cancer.3     
   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
   1st Qu.:0.2999   1st Qu.:0.2872   1st Qu.:0.2821  
   Median :0.6178   Median :0.6145   Median :0.4691  
   Mean   :0.5599   Mean   :0.5560   Mean   :0.4894  
   3rd Qu.:0.8411   3rd Qu.:0.8337   3rd Qu.:0.6917  
   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
  > 
  > bankObj <- createBank(bankMatrix)
  > summary(bankObj$rowStats)
        mean             SD              sdEst        
   Min.   :1.954   Min.   :0.01412   Min.   :0.04581  
   1st Qu.:2.470   1st Qu.:0.04578   1st Qu.:0.06954  
   Median :2.778   Median :0.06198   Median :0.07628  
   Mean   :2.745   Mean   :0.07515   Mean   :0.07518  
   3rd Qu.:3.016   3rd Qu.:0.08876   3rd Qu.:0.08209  
   Max.   :3.785   Max.   :0.50759   Max.   :0.08356  
  > dim(bankObj$background)
  [1] 2000   22
  > mean(bankObj$background)
  [1] 1.195464e-05
  > range(bankObj$background)
  [1] -14.91926  14.34338
  > 
  > bs2 <- bankStat(bankObj, testSet)
  > all(bs$nu.statistics == bs2$nu.statistics)
  [1] TRUE
  > 
  > proc.time()
     user  system elapsed 
     1.96    0.17    2.07