I sign up this website for this question. Suppose I have a vector 1 (all elements are 1) with $11^T-B$ positive definite, where $B$ is symmetric non-negative matrix (all elements are greater or equal to zero, but may not have inverse). Let $B\rightarrow 0$, can we say something about $1^T(11^T-B)^{-1}1$? I am supposing it converges to 1, but have no ideas. Any ideas would be appreciate.
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2$\begingroup$ I am not sure this question is research level, but anyway, what if you take $B = \epsilon\cdot 1 1^T$ for some small $\epsilon > 0$? Then $11^T - B = (1-\epsilon)11^T$ is not invertible. So what are you asking? $\endgroup$– Nik WeaverCommented Sep 20, 2016 at 22:09
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2$\begingroup$ @NikWeaver OP assumes that the difference is positive definite. Although it does seem that there might be no convergence. $\endgroup$– Alex DegtyarevCommented Sep 20, 2016 at 22:14
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$\begingroup$ @AlexDegtyarev: Oh, I see that. Okay, I can answer this. $\endgroup$– Nik WeaverCommented Sep 20, 2016 at 22:39
2 Answers
This is false. Consider the case of $2\times 2$ matrices. If we write $$ A=11^T-B = \begin{pmatrix} 1-a & 1-b \\ 1-b & 1-c \end{pmatrix} , $$ then a straightforward calculation shows that the quantity in question equals $$ \frac{2b-a-c}{\det A} = \frac{2b-a-c}{2b-a-c+ac-b^2} , $$ and this will go to $1$ if and only if $$ \frac{ac-b^2}{2b-a-c}\to 0 . \quad\quad\quad\quad (1) $$
Now it's easy to build a counterexample. We can take $a=t^{10}$, $c=2t$, $b=t+t^2$, and send $t\to 0+$. Notice that $\det A= t^2+O(t^3)>0$, so this satisfies the assumptions. However, (1) fails: the limit equals $-1/2$.
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$\begingroup$ That is awesome!!!! Then I have to find other method to derive the convergence... Basically I want to see in a Gaussian process, how the covariance matrix changes as all the points go to one point by using scaling the sampling space. I will try other methods to see whether any structure of $B$ would be helpful. Thank you so much for your awesome answer! $\endgroup$ Commented Sep 22, 2016 at 0:50
I believe the answer is yes, this converges to 1. It's a little subtle because if $B$ is small the eigenvalues of ${\bf 11}^T - B$ will be close to the eigenvalues of ${\bf 11}^T$, namely $1, 0, \ldots, 0$, and the eigenvector for the eigenvalue close to 1 will be close to the vector ${\bf 1}$, but after inverting $A = {\bf 11}^T - B$ its other eigenvalues will be large and it's not obvious how that affects ${\bf 1}^TA^{-1}{\bf 1}$.
Since this geometric picture didn't answer the question for me, I decided to look at a straight computation. The matrix entries of $A$ are $1 - b_{ij}$ and $A^{-1}$ has entries $\frac{1}{{\rm det}(A)}A_{ij}$ where $A_{ij}$ is the $i,j$-cofactor of $A$. This is relevant because ${\bf 1}^T A^{-1}{\bf 1}$ is just the sum of the entries of $A^{-1}$. So the question is what is $\frac{1}{{\rm det}(A)} \sum_{i,j} A_{ij}$? It seems to me that if the entries of $A$ are close to $1$ then both ${\rm det}(A)$ and $\sum_{i,j} A_{ij}$ vanish to order $n-2$ in the $b_{ij}$ where $n$ is the dimension and they are equal at order $n-1$. So as $B$ goes to zero the value of ${\bf 1}^T A^{-1}{\bf 1}$ will go to 1. But I won't try to write out the verification, which seems tedious but not difficult.
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$\begingroup$ Thank you for your reply! But I do not think things could be that easy since there maybe interactions of $det(A)$ and $\sum A_{ij}$, and $A_{ij}$ have different signs which make the numerator term more complicated. But that is a good point! $\endgroup$ Commented Sep 22, 2016 at 0:36
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$\begingroup$ I think it's right. Try working out the $2 \times 2$ and $3\times 3$ cases if you don't believe me. $\endgroup$ Commented Sep 22, 2016 at 5:06
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$\begingroup$ @NikWeaver: I think you're not paying enough attention to the details here. Did you see my answer, which I believe refutes what you claim? $\endgroup$ Commented Sep 22, 2016 at 5:21
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$\begingroup$ @ChristianRemling: ah, you're right. I was unconsciously assuming $2b - a - c \neq 0$ to first order in $\max(a,b,c)$. $\endgroup$ Commented Sep 22, 2016 at 10:11