When does the hessian matrix test fail. I understand we are testing the definiteness of the Matrix, and i also understand that because it's a symmetric $n•n$ matrix, we have a principal minor conditions for semi-definitness that we don't have with a non-symetric matrix. Please point out any errors i have made, answer the individual questions if you have time, and add anything you think i have missed. Thanks!
Negative Definite
- Principal minors Alternate in Sign with the first one being Negative.
- Note: For a $2•2$ matrix we can use either $h_{11}$ or $h_{22}$ as our first principal minor.
- Question: What if $h_{11}$ and $h_{22}$ have alternate signs?
- Question: How does this scale up to larger matrices. If so is it h_{nn} we can use as our first principal minor?
- Eigen values are all negative. This suggests that the trace will be negative as well?
- These conditions mean our function is Strictly Concave.
Negative Semi-Definite
- Principal minor conditions above but the Determinant can also be 0.
- Question: If our symmetric Matrix is grater than $2•2$ can more than one principal minor be equal to 0?
- Eigen Value conditions above but one (or more?) Eigenvalues can = 0
- Question: Can more than one eigenvalue = 0 for $n•n$ where $n>2$?
- Function is concave.
Positive Definite
- Principal minors > 0.
- Again for a $2•2$ matrix we can use either $h_{11}$ or $h_{22}$ as our first principal minor.
- Question: For a $2•2$ matrix what if $h_{11}$ is positive and $h_{22}$ negative?
- Question: Again, how does this scale up to larger matrices.
- Eigen values are all Positive?
- These conditions mean our function is Strictly Convex.
Positive Semi-Definite
- Principal minor conditions above but the Determinant can also be 0.
- Question: Same as before - If our symmetric Matrix is grater than $2•2$ can more than one principal minor be equal to 0?
- Eigen Value conditions above but one (or more?) Eigenvalues can = 0
- Question: Can more than one eigenvalue = 0 for $n•n$ when $n>2$?
- These conditions mean our function is convex.
Summary Questions
- When does the hessian test for a symmetric Matrix fail?
- More generally when does the tests on our Jacobin fail. E.g. say we are linearising around a fixed point in a system of differential equations ($\dot{x}, \dot{y}$), and so our second derivative in the Taylor series is the Jacobian. When we test the definitness of the Jacobian, under what conditions does this fail?
- Looking at the example $f(x,y) = 3xy$ the hessian for this example is.
- $H =\begin{bmatrix} 0 & 3 \\\ 3 & 0 \end{bmatrix}$
- Here we have $h_{11} = h_{22} = 0$ i have been told previously, that this function is quasiconcave but not concave. So this an example of the Hessian test failing?
- Are the statements above for Concavity and Convexity iff statements. I.e. If the function is Strictly Concave, it's hessian will be Negative Definite?