>> a = randn(500,5); >> x = 2*randn(5,1); >> y = (rand(500,1) < 1./(1+exp(-a*x))); >> xhat = logistic(a, y, [], [], struct('verbose', 1)) 1: [ -0.842889 -0.959492 0.843404 0.198022 0.199493 ] 2: [ -1.55055 -1.75901 1.57622 0.360507 0.398254 ] 3: [ -2.35678 -2.71685 2.4373 0.545032 0.62605 ] 4: [ -3.20879 -3.74533 3.35828 0.740927 0.854976 ] 5: [ -3.86696 -4.54162 4.0753 0.899695 1.02575 ] 6: [ -4.12265 -4.85136 4.35625 0.964904 1.09126 ] 7: [ -4.14969 -4.88416 4.38617 0.972078 1.09818 ] 8: [ -4.14995 -4.88447 4.38646 0.972149 1.09825 ] 9: [ -4.14995 -4.88447 4.38646 0.972149 1.09825 ] 10: [ -4.14995 -4.88447 4.38646 0.972149 1.09825 ] 11: [ -4.14995 -4.88447 4.38646 0.972149 1.09825 ] Converged. xhat = -4.1499 -4.8845 4.3865 0.9721 1.0982 >> x x = -3.9412 -4.0619 3.6705 1.1123 0.9645