So, the higher-order tests for extrema of single-variable functions and the hessian test (so, second derivative) for extrema of multivariable functions are quite well-known and studied by pretty much everyone.
However, I was wondering whether there was a variant of a higher-order test for multivariable functions, too. For example, f(x, y) = x^4 + y^4 clearly has a local minimum at the origin, yet the hessian test will obviously fail.
Is there such a test? Assuming existence and continuity of all the derivatives involved, of course. Some literature on the subject would also be quite nice!
#Higher-order tests for extrema of multivariable functions
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How about treating the Hessian as an operator $H =
\begin{bmatrix}
\frac{\partial^2}{\partial x^2} & \frac{\partial^2}{\partial x\partial y} \
\frac{\partial^2}{\partial y\partial x} & \frac{\partial^2}{\partial y^2}
\end{bmatrix}$
Djake3tooth
And looking at the eigenvalues of $Hf, H^2f, \dots$
Djake3tooth
There's also the higher-order derivative tensor
https://www.quora.com/As-there-is-a-Jacobian-and-Hessian-matrix-is-there-a-third-partial-derivative-matrix
Quora
Answer (1 of 2): Yes, there is a third partial derivative matrix called the "third-order derivative tensor" or "third-order partial derivative matrix."
The third-order derivative tensor is a three-dimensional array of partial derivatives that describes the third-order derivatives of a scalar fun...
But I don't know if you can extract out of that tensor if there are local minima/maxima or sadle points
Sadly enough, this method gets fooled by functions like
$f(x,y)=x^4+x^2y^2+y^4+xy^3$
Djake3tooth
because $H^2$ doesn't contain every possible combination of 4 partial derivatives
Djake3tooth