Non-linear regression results, obtained by iterating an approximating linear system. Observe how the estimates are tending towards zero, and how the SEs are converging to the values given by the non-linear regression program.
Linear Regression: Estimate SE Prob Variable 0 4.138723E-2 (2.91773) 0.98899 Variable 1 1.91031 (3.50720) 0.59921 Variable 2 4.688609E-2 (0.138536) 0.74279 R Squared: 0.119552 Sigma hat: 2.12964 Number of cases: 12 Degrees of freedom: 9 (124.42338723437011 21.334959074739725 2.174555336396219) Linear Regression: Estimate SE Prob Variable 0 -3.992119E-2 (2.86921) 0.98920 Variable 1 0.183860 (3.94951) 0.96389 Variable 2 2.823019E-3 (0.140285) 0.98438 R Squared: 3.655313E-3 Sigma hat: 2.12887 Number of cases: 12 Degrees of freedom: 9 (124.38346604819884 21.51881954326433 2.1773783557662942) Linear Regression: Estimate SE Prob Variable 0 -1.527102E-3 (2.87184) 0.99959 Variable 1 4.060895E-3 (3.99513) 0.99921 Variable 2 1.058519E-4 (0.140502) 0.99942 R Squared: 0.000000 Sigma hat: 2.12887 Number of cases: 12 Degrees of freedom: 9 (124.38193894645649 21.522880438343165 2.1774842077153984) Linear Regression: Estimate SE Prob Variable 0 7.135111E-7 (2.87169) 1.00000 Variable 1 1.043788E-5 (3.99612) 1.00000 Variable 2 2.251319E-7 (0.140507) 1.00000 R Squared: 0.000000 Sigma hat: 2.12887 Number of cases: 12 Degrees of freedom: 9 (124.38193965996763 21.522890876219947 2.177484432847311) Linear Regression: Estimate SE Prob Variable 0 -2.201135E-8 (2.87169) 1.00000 Variable 1 6.411643E-8 (3.99613) 1.00000 Variable 2 1.922862E-9 (0.140507) 1.00000 R Squared: 0.000000 Sigma hat: 2.12887 Number of cases: 12 Degrees of freedom: 9 (124.38193963795628 21.522890940336374 2.177484434770173) Linear Regression: Estimate SE Prob Variable 0 1.405989E-10 (2.87169) 1.00000 Variable 1 -5.322782E-11 (3.99613) 1.00000 Variable 2 -3.853513E-12 (0.140507) 1.00000 R Squared: 0.000000 Sigma hat: 2.12887 Number of cases: 12 Degrees of freedom: 9 (124.38193963809688 21.522890940283148 2.1774844347663196)