[R] var-covar matrices comparison:

[Aldi Kraja]

Hi,
Using package gclus in R, I have created some graphs that show the 
trends within subgroups of data and correlations among 9 variables (v1-v9).
Being interested for more details on these data I have produced also the 
var-covar matrices.
Question: From a pair of two subsets of data (with 9 variables each, I 
have two var-covar matrices for each subgroup, that differ for a 
treatment on one group (treatment A) vs (non-Treatment A).

Is there a software that can compare if two var-covar matrices are 
statistically the same?

Below are a pair of two matrices, from several others.
Thank you in advance for any input.
Aldi

 First group var-covar matrix (the data were under treatment a)

v1        v2                 v3          v4               v5       
v6       v7            v8             v9

 

v1         730.87       3.406      -283.41        -74.68       
107.57      -1355.13      -112.46      14.000       5.776

v2             3.41      24.950       105.45       -121.31      
-307.68       -285.40        29.65      -2.500      -7.796

v3          -283.41     105.451      6292.19      -2676.46      
-970.80      29296.23     10715.29       3.156     -66.313

v4           -74.68    -121.307     -2676.46     124492.30     
-2289.47     -20377.34      -409.71     183.500     563.102

v5           107.57    -307.681      -970.80      -2289.47      
7045.62      12118.09       954.51      38.258      96.355

v6         -1355.13    -285.404     29296.23     -20377.34     
12118.09     218555.93     70126.71     137.000    -130.667

v7          -112.46      29.645     10715.29       -409.71       
954.51      70126.71     28239.57      67.989     -26.370

v8            14.00      -2.500         3.16        183.50        
38.26        137.00        67.99      24.500       9.000

v9             5.78      -7.796       -66.31        563.10        
96.35       -130.67       -26.37       9.000      22.776

 

 

 Second group var-covar matrix (the data were NOT under treatment a)

v1        v2                 v3          v4               v5       
v6       v7            v8             v9

 

v1          2696.25       27.05       201.06       2745.54      
-344.39        540.48        654.20      34.363       7.623

v2            27.05       86.37       -96.89       -497.28     
-1185.10      -3108.71       -910.38      -4.254      -9.115

v3           201.06      -96.89     10647.26       8378.07      
 595.81      66122.43      26237.21     -65.093     -51.998

v4          2745.54     -497.28      8378.07     408391.25     
-3887.28      40477.40      30652.01     450.539      50.311

v5          -344.39    -1185.10       595.81      -3887.28     
29204.00      65320.00      15238.41     -98.237     102.975

v6           540.48    -3108.71     66122.43      40477.40     
65320.00     549955.14     194691.90    -555.552     -95.210

v7           654.20     -910.38     26237.21      30652.01     
15238.41     194691.90      82698.88     -70.417     -75.585

v8            34.36       -4.25       -65.09        450.54       
-98.24       -555.55        -70.42      79.689       8.164

v9             7.62       -9.11       -52.00         50.31       
102.97        -95.21        -75.58       8.164      30.492