Additional Information
Model: y = f(x;beta) + e = (beta(1)(x^2 + xbeta(2)) + (x^2 + xbeta(3) + beta(4)) + e
This problem was found to be difficult for some very good algorithms. There is a local minimum at (+inf, -14.07..., -inf, -inf) with final sum of squares .00102734.... See More, J. J., Garbow, B. S., and Hillstrom, K. E. (1981). Testing unconstrained optimization software. ACM Transactions on Mathematical Software. 7(1): pp. 17-41.