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Inverse Matrix of X^T X: Necessary and Sufficient Conditions 📂Matrix Algebra

Inverse Matrix of X^T X: Necessary and Sufficient Conditions

Theorem

Suppose that the matrix XRm×nX \in \mathbb{R}^{m \times n} is given and mnm \ge n, then the following holds: (XTX)1    rankX=n \exists \left( X^{T} X \right)^{-1} \iff \text{rank} X = n In other words, the necessary and sufficient condition for the inverse matrix of XTXX^{T} X to exist is that XX has full rank.


Explanation

The reason this fact is important is that in overdetermined systems like y=Xβ\mathbf{y} = X \beta in multiple regression analysis, you often need to perform calculations such as β=(XTX)1XTy \beta = \left( X^{T} X \right)^{-1} X^{T} \mathbf{y} …not just often, but really a lot. Situations where one encounters problems due to not knowing this fact, or forgetting it during actual analysis, are also quite common.

Proof 1

(    )(\implies)

If the inverse of XTXRn×nX^{T} X \in \mathbb{R}^{n \times n} exists, then it is rankXTX=n\text{rank} X^{T} X = n. n=rankXTXrankXmin{n,m}n \begin{align*} n =& \text{rank} X^{T} X \\ \le & \text{rank} X \\ \le & \min \left\{ n , m \right\} \\ \le & n \end{align*} For the above inequality to hold, it must be rankX=n\text{rank} X = n.


(    )(\impliedby)

For some uRn\mathbf{u} \in \mathbb{R}^{n}, let XTXu=0 X^{T} X \mathbf{u} = \mathbf{0} Let us assume that u=0\mathbf{u} = \mathbf{0}, which is equivalent to the existence of (XTX)1\left( X^{T} X \right)^{-1}. We need to show that u\mathbf{u} is a zero vector. Since Rn\mathbb{R}^{n} is an inner product space, we can calculate the vector dot product of XTXuX^{T} X \mathbf{u} and 0\mathbf{0}: <,>\left< \cdot , \cdot \right>. As this is the inner product of zero vectors, it is obviously 00, and we obtain 0=<XTXu,u>=(XTXu)Tu=uTXTXu=(Xu)TXu=<Xu,Xu> \begin{align*} 0 =& \left< X^{T} X \mathbf{u} , \mathbf{u} \right> \\ =& \left( X^{T} X \mathbf{u} \right)^{T} \mathbf{u} \\ =& \mathbf{u}^{T} X^{T} X \mathbf{u} \\ =& \left( X \mathbf{u} \right)^{T} X \mathbf{u} \\ =& \left< X \mathbf{u} , X \mathbf{u} \right> \end{align*} This implies Xu=0X \mathbf{u} = \mathbf{0}. Given that XX is assumed to have full rank, it must be u=0\mathbf{u} = \mathbf{0}.

See Also