I want to calculate the inverse of a real and symmetric matrix when I remove the first row and the first column from it using the Woodbury formula (as is described here). However, in my case, while $A−UV$ is invertible, $−I+VA^{−1}U$ is not. Is there another way to compute the inverse of the updated matrix?
More explanation:
I quote a part of this post here:
$$ A = \begin{bmatrix} a & v_1 & v_2 & v_3 \\ u_1 & & & \\ u_2 & & B & \\ u_3 & & & \end{bmatrix} $$ we can take $U = \begin{bmatrix} 1 & 0 \\ 0 & u_1 \\ 0 & u_2 \\ 0 & u_3 \end{bmatrix}$ and $V = \begin{bmatrix} 0 & v_1 & v_2 & v_3 \\ 1&0&0&0 \end{bmatrix}$, so that: $$ UV = \begin{bmatrix} 0 & v_1 & v_2 & v_3 \\ u_1 & 0 & 0 & 0 \\ u_2 & 0 & 0 & 0 \\ u_3 & 0 & 0 & 0 \end{bmatrix} $$ Then $A - UV = \begin{bmatrix} a & 0 \\ 0 & B \end{bmatrix}$ and provided $a \neq 0$ the update can be done by inverting $(I - VA^{-1}U)$, a $2\times 2$ matrix.
In my example, $a$ can be zero, and matrix $A$ is symmetric, thus $v_i = u_i$. Also the upper left element of $A^{-1}$ is zero. I define $U = \begin{bmatrix} 1 & 0 \\ 0 & u_1 \\ 0 & u_2 \\ 0 & u_3 \end{bmatrix}$ and $V = \begin{bmatrix} b & u_1 & u_2 & u_3 \\ 1&0&0&0 \end{bmatrix}$, $b\neq 0$. So:
$$ A - UV = \begin{bmatrix} a-b & 0 & 0& 0\\ 0& & & \\ 0& & B & \\ 0& & & \end{bmatrix} $$ and thus:
$$ (A - UV)^{-1} = \begin{bmatrix} (a-b)^{-1} & 0 & 0& 0\\ 0& & & \\ 0& & B^{-1} & \\ 0& & & \end{bmatrix} $$
and $$\left(A-UV \right)^{-1} = A^{-1} - A^{-1}U \left(-I+VA^{-1}U \right)^{-1} VA^{-1}$$ but regardless of the value of $b$, the $2\times 2$ matrix $I - VA^{-1}U$ is always not invertible. Is there a trick or another way to solve this problem?