A zero mean vector [B]2x1 is unitarily 1 V3 1 B, -1 3 transformed. Given A = and Ru= 0 < p< 1. Obtain covariance matrix RA. Also obtain correlation between A(0) and A(1), if p=0.95.
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- We fit a ridge regression model to some data for λ=10 and λ=100 and we obtain the coefficients vector estimates b1 and b2 respectively. Then b1 is either more sparse than b2, or as sparse as b2. b2 is either more sparse than b1, or as sparse as b1. The L2 norm of b2 is less or equal to the L2 norm of b1. The L2 norm of b1 is less or equal to the L2 norm of b2.Find a basis B of P3, the vector space of polynomials of degree ≤3, so that the transition matrix from B to the standard basis S={1,x,x2,x3} isLet T: V-->W be a linear transformation between finite-dimensional vector spaces V and W Let B and C be bases for V and W, respectively, and let A= [ T]C<--B. Use the results of this section to give a matrixbased proof of the Rank Theorem