2 replaced http://mathematica.stackexchange.com/ with https://mathematica.stackexchange.com/ edited Apr 13 '17 at 12:55 Using ExperimentalNumericalFunction frameworkExperimentalNumericalFunction framework directly (FindMinimum uses it under the hoodFindMinimum uses it under the hood) it is straightforward to get the numerical approximation of the Hessian: f = ExperimentalCreateNumericalFunction[{x, y}, Cos[x^2 - 3 y] + Sin[x^2 + y^2], {1}, Hessian -> FiniteDifference]; f["Hessian"[{1.376384972443001, 1.6786760817546214}]]  {{{15.1555, 0.983708}, {0.983708, 20.2718}}} Using ExperimentalNumericalFunction framework directly (FindMinimum uses it under the hood) it is straightforward to get the numerical approximation of the Hessian: f = ExperimentalCreateNumericalFunction[{x, y}, Cos[x^2 - 3 y] + Sin[x^2 + y^2], {1}, Hessian -> FiniteDifference]; f["Hessian"[{1.376384972443001, 1.6786760817546214}]]  {{{15.1555, 0.983708}, {0.983708, 20.2718}}} Using ExperimentalNumericalFunction framework directly (FindMinimum uses it under the hood) it is straightforward to get the numerical approximation of the Hessian: f = ExperimentalCreateNumericalFunction[{x, y}, Cos[x^2 - 3 y] + Sin[x^2 + y^2], {1}, Hessian -> FiniteDifference]; f["Hessian"[{1.376384972443001, 1.6786760817546214}]]  {{{15.1555, 0.983708}, {0.983708, 20.2718}}} 1 answered Jul 15 '14 at 6:04 Alexey Popkov 39.9k44 gold badges113113 silver badges274274 bronze badges Using ExperimentalNumericalFunction framework directly (FindMinimum uses it under the hood) it is straightforward to get the numerical approximation of the Hessian: f = ExperimentalCreateNumericalFunction[{x, y}, Cos[x^2 - 3 y] + Sin[x^2 + y^2], {1}, Hessian -> FiniteDifference]; f["Hessian"[{1.376384972443001, 1.6786760817546214}]] ` {{{15.1555, 0.983708}, {0.983708, 20.2718}}}