I'm solving an exercise problem and was facing some confusion regarding how to solve it. The problem is (roughly translated to English):
Given the following:
$$\mathbf{A} = \begin{bmatrix} 2 & 0 \\ 1 & 1 \\ 0 & 1 \end{bmatrix},\ \mathbf{w} = \begin{bmatrix} 1 \\ 1 \\ 1 \end{bmatrix}$$
There exists no vector $\mathbf{x} = (x, y)$ that satisfies $\mathbf{A} \mathbf{x} = \mathbf{w}$. Find the values of $x$ and $y$ that minimize the distance between $\mathbf{A}\mathbf{x}$ and $\mathbf{w}$ in $\mathbb{R}^3$.
My Approach
The result of $\mathbf{A}\mathbf{x}$ is $(2x, x + y, y)$. Since we're minimizing distance in $\mathbb{R}^3$ I thought that finding the minima for the following would do the trick:
$$ \begin{align} d & = (2x - 1)^2 + (x + y - 1)^2 + (y - 1)^2 \\ & = 5x^2 - 6x + 2xy + 2y^2 - 4y + 2 \end{align} $$
This is where my confusion mainly stems from, but in order to get the values for both the $x$ and $y$ coordinates, I obtained the partial derivatives of the above equation and set them to $0$.
$$ \begin{align} & \frac{\partial d}{\partial x} = 10x - 6 + 2y \\ & \frac{\partial d}{\partial y} = \phantom{0}2x + 4y - 4 \end{align} $$
Setting both of these to $0$ and solving gives us:
$$ x = \frac{4}{9},\ y = \frac{7}{9} $$
Is this approach correct? Any tips are appreciated. Thanks.
Yes, your approach is completely correct.
For what it's worth, we can systematically obtain "least squares" solutions to such equations by solving the equation $A^TA \mathbf x = A^T \mathbf w$.