nag_correg_corrmat (g02bxc) Example Program Results

Case 1 --- Using weights

Input data
   0.9   0.1   0.9   9.1
   0.0   0.0   0.1   3.7
   0.1   1.3   0.4   4.5

Sample means.
   0.5
   0.4
   0.6

Standard deviation.
   0.4
   0.6
   0.3

Correlation matrix.
   1.0000    -0.4932     0.9839  
  -0.4932     1.0000    -0.3298  
   0.9839    -0.3298     1.0000  

Variance matrix.
    0.197     -0.123      0.149  
   -0.123      0.316     -0.063  
    0.149     -0.063      0.117  

Sum of weights   17.3

Case 2 --- Using weights

Input data
   9.1   3.7   4.5   0.1
   0.9   0.1   0.9   1.3
   0.0   0.0   0.1   0.4

Sample means.
   1.3
   0.3
   1.0

Standard deviation.
   3.3
   1.4
   1.5

Correlation matrix.
   1.0000     0.9908     0.9903  
   0.9908     1.0000     0.9624  
   0.9903     0.9624     1.0000  

Variance matrix.
   10.851      4.582      5.044  
    4.582      1.971      2.089  
    5.044      2.089      2.391  

Sum of weights    1.8

Case 3 --- Not using weights

Input data
   1.1   0.1   9.7   0.7
  11.1  23.5  11.1   9.4
   0.9   9.0   8.7   0.0

Sample means.
   4.4
  10.9
   9.8

Standard deviation.
   5.8
  11.8
   1.2

Correlation matrix.
   1.0000     0.9193     0.9200  
   0.9193     1.0000     0.6915  
   0.9200     0.6915     1.0000  

Variance matrix.
   33.951     63.208      6.485  
   63.208    139.250      9.871  
    6.485      9.871      1.464  

Sum of weights    3.0

Case 4 --- Using weights

Input data
   1.1   0.1   9.7   0.7
  11.1  23.5  11.1  19.4
   0.9   9.0  78.7   0.0

Sample means.
  10.7
  22.7
  11.1

Standard deviation.
   1.9
   4.5
   1.8

Correlation matrix.
   1.0000     0.9985     0.0173  
   0.9985     1.0000     0.0716  
   0.0173     0.0716     1.0000  

Variance matrix.
    3.672      8.538      0.059  
    8.538     19.909      0.570  
    0.059      0.570      3.185  

Sum of weights   20.1

Case 5 --- Not using weights

Input data
   1.1   0.1   9.7   0.7
  11.1   3.5  13.1  19.4
   0.9   0.0  78.7   0.0

Sample means.
   4.4
   1.2
  33.8

Standard deviation.
   5.8
   2.0
  38.9

Correlation matrix.
   1.0000     0.9999    -0.4781  
   0.9999     1.0000    -0.4881  
  -0.4781    -0.4881     1.0000  

Variance matrix.
   33.951     11.567    -108.343  
   11.567      3.941    -37.687  
  -108.343    -37.687    1512.750  

Sum of weights    3.0

Case 6 --- Using weights

Input data
   1.1   0.1   9.7   0.7
  17.1  93.5  13.1  19.4
  30.9   0.0  78.7   0.9

Sample means.
  17.2
  86.3
  15.9

Standard deviation.
   4.2
  25.6
  13.7

Correlation matrix.
   1.0000    -0.0461     0.7426  
  -0.0461     1.0000    -0.7033  
   0.7426    -0.7033     1.0000  

Variance matrix.
   17.846     -4.989     43.123  
   -4.989    656.407    -247.692  
   43.123    -247.692    188.970  

Sum of weights   21.0