In the application of least-squares regression to data fitting, the quantity of minimization is the sum of squares (sum of squared errors, to be specific). I believe this fitting also minimizes the root-mean-square error because square root is a monotonic function. However, I was not able immediately to find published sources stating this.
Does anyone disagree with me, i.e., is there a flaw in my reasoning?