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. 2004 Sep 14;1:8. doi: 10.1186/1742-4682-1-8

Table 3.

Comparison of the different linearization options (I, II and IV)

I. Absolute deviation II. Relative deviation IV. Lotka-Volterra
a10 0.0000 0.0000 14.4748
a11 -14.3647 -14.3647 -18.9581
a12 -0.1466 -0.1466 -0.6836
a13 5.3878 7.3414 7.3367
a14 -0.1712 -0.2165 -0.4694
a15 -5.6702 -7.1723 -7.4981
a20 0.0000 0.0000 0.0144
a21 14.6119 14.6119 19.8910
a22 -14.6540 -14.6540 -19.9277
a23 -0.0006 -0.0009 -0.0001
a24 0.0390 0.0494 0.0472
a25 -0.0245 -0.0309 -0.0335
a30 0.0000 0.0000 26.4020
a31 -3.2058 -2.3527 2.8725
a32 1.9062 1.3989 -1.7989
a33 -27.9204 -27.9204 -26.6164
a34 1.8842 1.7491 -1.5871
a35 -1.0724 -0.9955 0.9692
a40 0.0000 0.0000 8.0270
a41 2.6365 2.0843 6.3364
a42 -1.3820 -1.0925 -4.1579
a43 17.6654 19.0295 19.0005
a44 -20.2112 -20.2112 -23.1319
a45 -8.3594 -8.3594 -7.7047
a50 0.0000 0.0000 0.0869
a51 -0.5092 -0.4026 -0.6617
a52 0.1751 0.1384 0.4441
a53 -0.0055 -0.0059 -0.0003
a54 18.8987 18.8987 20.2939
a55 -18.7852 -18.7852 -20.2152

Estimated coefficients for three of the linearization approaches: absolute deviation from steady state (left column), relative deviation from steady state (center column) and Lotka-Volterra linearization (right column). The dataset consisted of 401 data points in the interval [0,4] and resulted from a simulation in which X3 was perturbed at t = 0 to a value 5% above its steady-state value.