Can you help me to l1 regularized least squares applying LASSO problem with

the soft thresholding operation? I attached the reference

Exercise 6. We are trying to find a solution to an 61 regularized least squares from the following data matrix -1 3 X = -3 and measurements y = (-4.9, -0.8, -8.9, 4.9, 1.1, -2.0) 7. Compute the LASSO optimal solution with 1 = 10.min IXB - yl13 + AllBl/1 BERd is given by B( ) ) = SA (B (2 ) where S is the soft thresholding operation defined component wise as Sx (t) = sign(t) t - 1, 0]+ = sign (t) max { t - 1, 0} and where (2 = (X X)-1XTy = XTy denotes the classical regression estimator