Issue with Jama's Eigenvalue decomposition fun

Question

I am getting a wrong eigen-vector (also checked by running multiple times to be sure) when i am using matrix.eig(). The matrix is:

1.2290 1.2168 2.8760 2.6370 2.2949 2.6402
1.2168 0.9476 2.5179 2.1737 1.9795 2.2828
2.8760 2.5179 8.8114 8.6530 7.3910 8.1058
2.6370 2.1737 8.6530 7.6366 6.9503 7.6743
2.2949 1.9795 7.3910 6.9503 6.2722 7.3441 
2.6402 2.2828 8.1058 7.6743 7.3441 7.6870

The function returns the eigen vectors:

-0.1698  0.6764  0.1442 -0.6929 -0.1069  0.0365
-0.1460  0.6478  0.1926  0.6898  0.0483 -0.2094
-0.5239  0.0780 -0.5236  0.1621 -0.2244  0.6072
-0.4906 -0.0758 -0.4573 -0.1279  0.2842 -0.6688
-0.4428 -0.2770  0.4307  0.0226 -0.6959 -0.2383
-0.4884 -0.1852  0.5228 -0.0312  0.6089  0.2865

Matlab gives the following eigen-vector for the same input:

0.1698 -0.6762 -0.1439  0.6931  0.1069  0.0365
0.1460 -0.6481 -0.1926 -0.6895 -0.0483 -0.2094
0.5237 -0.0780  0.5233 -0.1622  0.2238  0.6077
0.4907  0.0758  0.4577  0.1278 -0.2840 -0.6686
0.4425  0.2766 -0.4298 -0.0227  0.6968 -0.2384
0.4888  0.1854 -0.5236  0.0313 -0.6082  0.2857

The eigen-values for matlab and jama are matching but eigen-vectors the first 5 columns are reversed in sign and only the last column is accurate.

Is there any issue on the kind of input that Jama.Matrix.EigenvalueDecomposition.eig() accepts or any other problem with the same? Please tell me how i can fix the error. Thanks in advance.

Answer 1

There is no error here, both results are correct - as is any other scalar times the eigen vectors.

There are an infinite number of eigen vectors that work - its just convention that most software programs report the vectors that have length of one. That Jama reports eigen vectors equal to -1 times those of Matlab is probably just an artifact of the algorithm they used.