You fit Model 1: y ~ X1 + X2. You also fit Model 2 using Z = [X1 − X2, X1 + X2] = X T where T = [[1,1], [−1,1]] (2×2, invertible). a) Prove that OLS predictions ŷ are identical for Model 1 and Model 2 for any invertible T; derive the mapping between coefficients (b_Z = T^{-1} b_X). b) If you use ridge (λ||b||₂²) or lasso (λ||b||₁) instead of OLS, will coefficients and predictions remain invariant under this T? Specify conditions precisely (e.g., ridge invariance to orthonormal transforms but not arbitrary scalings; lasso invariance only to signed permutations, not general rotations). c) For ridge, write solutions and show when ŷ is unchanged; for lasso, provide a concrete counterexample where predictions differ.