> #3.8 Catfood Example
> 
> x<-rbind(
+ c(2,1,2,2),
+ c(3,4,1,4),
+ c(3,2,2,3),
+ c(2,1,1,3),
+ c(3,2,5,5),
+ c(2,2,2,4),
+ c(1,3,2,3),
+ c(3,3,3,4),
+ c(3,4,1,4),
+ c(4,4,2,5),
+ c(3,5,2,2),
+ c(3,1,3,5),
+ c(4,5,1,5),
+ c(1,5,1,5),
+ c(3,2,3,4),
+ c(3,4,3,4),
+ c(3,1,2,2),
+ c(1,3,1,3),
+ c(1,3,1,3),
+ c(1,5,3,2))
> colnames(x)<-c("A","B","C","D")
> 
> xtotab(x)
         [,1]     [,2]     [,3]       [,4]
[1,] 4.666667 8.500000 5.000000  1.8333333
[2,] 6.666667 2.166667 5.166667  6.0000000
[3,] 8.166667 7.000000 4.000000  0.8333333
[4,] 0.500000 2.333333 5.833333 11.3333333
> U(x)
           [,1]       [,2]       [,3]       [,4]
[1,] 15.1666667  4.1666667  0.6666667  0.0000000
[2,]  4.1666667 12.5000000  3.0000000  0.3333333
[3,]  0.6666667  3.0000000 11.0000000  5.3333333
[4,]  0.0000000  0.3333333  5.3333333 14.3333333
> BlockAnalysis(x)
$Cri
    Location Dispersion
A -1.1372832 -1.9873333
B  0.0947736  1.5004562
C -2.3693401 -0.6041089
D  3.4118497  1.0909859

$partition
           df        SS       pvalue
Location    3 18.556886 0.0003375728
Dispersion  3  7.756060 0.0513316268
Residual    3  2.557116 0.4650573162
Total       9 28.870063 0.0006815624

>