> #4.6.2 Ice Cream (Vanilla Flavour) Example
> x<-matrix(c(
+ 2,4,0,3,NA,NA,
+ 0,4,3,NA,5,NA,
+ 0,3,4,NA,NA,5,
+ 1,3,NA,4,5,NA,
+ 0,2,NA,4,NA,5,
+ 0,1,NA,NA,4,5,
+ 2,NA,3,1,4,NA,
+ 0,NA,0,3,NA,4,
+ 0,NA,2,NA,3,3,
+ 2,NA,NA,4,1,4,
+ NA,0,2,3,1,NA,
+ NA,1,1,2,NA,4,
+ NA,2,3,NA,5,4,
+ NA,1,NA,4,5,2,
+ NA,NA,4,3,1,2),ncol=6,byrow=T)
> colnames(x)<-c("A","B","C","D","E","F")
> 
> # Note that 1 is added to the numbers to meet the data structure requirements
> xtotab(x+1)
    1   2   3   4
A 6.5 3.5 0.0 0.0
B 3.5 4.5 1.0 1.0
C 2.0 4.0 3.0 1.0
D 1.0 0.0 7.5 1.5
E 2.0 1.0 1.5 5.5
F 0.0 2.0 2.0 6.0
> U(x+1)
   1  2  3  4
1 14  1  0  0
2  1 14  0  0
3  0  0 14  1
4  0  0  1 14
> BlockAnalysis(x+1)
$Cri
    Location Dispersion
A -3.0096876  0.9302605
B -1.4394158 -0.3100868
C -0.5234239 -1.2403473
D  1.1777038 -1.5504342
E  1.4394158  1.5504342
F  2.3554077  0.6201737

$partition
           df        SS       pvalue
Location    5 20.410959 0.0010461345
Dispersion  5  7.692308 0.1740283180
Residual    5 10.922374 0.0529409783
Total      15 39.025641 0.0006352248

>