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Compute the mean square error between \(X_t\) and \(Y_t\), as $$\frac{1}{n} \sum_{k=1}^n \|X_k-Y_k\|^2,$$ where \(\|\cdot\|\) denotes a Euclidian norm and \(n\) is the number of observations.
MSE(X, Y)
first matrix to compare
second matrix to compare
Estimated mean square error