Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matr...
1. (20 points) Let X (Xi, X, Xs) be a real random vector, where X, are identically dis- tributed and independent (ii.d.) zero-mean Gaussian real random variables. Consider the random vector Y given by where A is a 3 x 3 real matrix and b is a 3 x 1 real vector. Justify all your answers. (a) Find the covariance matrix Cx of x. (b) Find the mean vector EY] of Y (c) Express the covariance matrix Cy of Y...
1.4 Suppose x is a random vector drawn from a d-dimensional multivariate Gassian distribution with mean 0 and covariance Σ Define y := Qx + u, for a known (invertible) d × d matrix Q, and a dx 1 vector v. What is the distribution of y?
5. Let be a normal random vector with the following mean and covariance matrices: 2 Let also Y; Y3 where (a) Find P(X2 >0). b Find my EY]. the expected value vector of Y. (c) Find CY, the covariance matrix of Y d) Find P(Y 2). 5. Let be a normal random vector with the following mean and covariance matrices: 2 Let also Y; Y3 where (a) Find P(X2 >0). b Find my EY]. the expected value vector of Y....
Let V be a m-dimensional Gaussian random vector with zero-mcan and covariance In. Let X = ЛⅤ and Y = CV. Find E(X | Y). TL - Let V be a m-dimensional Gaussian random vector with zero-mcan and covariance In. Let X = ЛⅤ and Y = CV. Find E(X | Y). TL -
12. Let X be a random vector with mean y and covariance , also let A be a fixed (deterministic) matrix. Prove that E [X'AX] = tr(AE) + M'Aj
Let x ER" be a Gaussian random vector with mean 0 and covariance matrix I. Prove that, for any orthogonal matrix (ie, an n × n matrix satisfying UTU-1), one has that Ur and are identically distributed.
As on the previous page, let Xi,...,Xn be i.i.d. with pdf where >0 2 points possible (graded, results hidden) Assume we do not actually get to observe X, . . . , Xn. to estimate based on this new data. Instead let Yİ , . . . , Y, be our observations where Yi-l (X·S 0.5) . our goals What distribution does Yi follow? First, choose the type of the distribution: Bernoulli Poisson Norma Exponential Second, enter the parameter of...
Suppose that x is a p-dimensional random vector with mean y and covariance ? = UDUt where U = Ui U2 ... Up li dz ... D = de with u1,...,Up orthonormal. Show that S di Cov(u: (x – u), uf(x – u)) = { 0 i= otherwise
is an eigenvalue invertible matrix with X as an eigenvalue. Show that of A-1. Suppose v ER is a nonzero column vector. Let A (a) Show that v is an eigenvector of A correspond zero column vector. Let A be the n xn matrix vvT. n eigenvector of A corresponding to eigenvalue = |v||2. lat O is an eigenvalue of multiplicity n - 1. (Hint: What is rank A?) (b) Show that 0 is an eigenvalue of
The vector-matrix form of the system model is: (18 0 18000 72001 x f(t) or Mx + Kx = f(t) 08.3. -7200 8000 | X, 3. (1) X= M = (18 0 08 K 18000 -7200 7200 8000 and f(t) = (1) 12(0)] [x₂(t) The system's eigenvalues, natural frequencies, and eigenvectors are: 1 2 = 400, 0, = 20 s', and v, 1.5 1.) = 1600, 0), = 40 s', and v, = -1.5 1 1 The inverse of modal...