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Assume that Y is a 3 × 1 random vector with mean vector ,y...
11 a12 13 11 021 C11 C12 C13 a31 a32 a33 1)13 123 C31 C32 C33...
11 a12 13 11 021 C11 C12 C13 a31 a32 a33 1)13 123 C31 C32 C33 Assume that Y is a 3 1 random vector with mean vector μΥ- 1-1 and covariance matrix ΣΥΥ-σ2, I. Assume that e is an independent random variable variable with zero mean and variance φ2 4, Derive the mean and variance for W = [1-2 1] . Y +e. 5. Derive the covariance matrix between W and Y 6. Derive the correlation matrix between Wand...
ρρ 4. The correlation matrix of the random variables Y,,Y,,Y,, Y4 is 12 3 0 < ρ < l , and each ra...
Please explain how to get variance covariance matrix and how to
get the final solution:
ρρ 4. The correlation matrix of the random variables Y,,Y,,Y,, Y4 is 12 3 0 < ρ < l , and each random variable has variance σ2 . Let W1-Y1 +Ý, +Ý, , and let W2 Y +Y +Y,. Find the variance covariance matrix of (W,W2) Jo 1 1 01 L : I :).andi Solution: The matrix M of the linear transformations is M =...
Consider a random vector Y () y(2). y(k) where the elements y(i) are made yi)wi), j-1,...
Consider a random vector Y () y(2). y(k) where the elements y(i) are made yi)wi), j-1, ...k where w(j) are independent, identically distributed, Gaussian, zero-mean, and with the variance σ2 i.e., N(0, σ2). 1. Find the Maximum Likelihood (ML) estimator for xr, i.e., ML 2. Find the Mean Square Error (MSE) of ML estimator, i.e., MSE(XML) Ξ Var@sL) 3. Is this estimator consistent? Prove your answer 4. Is this estimator efficient? Prove your answer
Let X be a random variable with mean μ and variance σ2, and let Y be...
Let X be a random variable with mean μ and variance σ2, and let Y be a random variable with mean θ and variance τ2, and assume X and Y are independent. (a) Determine an expression for Corr(X Y , Y − X ). (b) Under what conditions on the means and variances of X and Y will Corr(XY, Y −X) be positive (i.e., > 0 )?
2) Two statistically-independent random variables, (X,Y), each have marginal probability density,...
2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector,
2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector,
Problem 3: 10 points σ2. Define Assume that U, V, and W are independent random variables...
Problem 3: 10 points σ2. Define Assume that U, V, and W are independent random variables with the same common variance X= + W and Y-V-W. 1. Find the variances Var[X] and Var[Y 2. Find the covariance between X and Y, that is: cov [x,Y 3. Find the covariance between (X+Y) and (X - Y), that is: COV[(X +Y), (X -Y)]
Let Y = (Yİ Y2 Yn)' be a random vector taking on values in Rn with...
Let Y = (Yİ Y2 Yn)' be a random vector taking on values in Rn with mean μ E Rn and covariance matrix 2. Also let 1 be the ones vector defined by 1-(1 1) 5.i Find the projection matrix Hy where V is the subspace generated by 1 5.ii Show that Hy is symmetric and idempotent. 5.iii Let x = (a a . .. a)', where a E Rn. Show that Hvx = x. 5.iv Find the projection of...
Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matr...
Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matrix vv1 , for some vector v ER 1point possible (graded) Let v = . (i.e., v is the normalized version of v). What is the variance of v X? (If applicable, enter trans(v) for the transpose v of v, and normv) for the norm |vll of a vector v.) Var (V STANDARD NOTATION SubmitYou have used 0...
. Suppose that Y is a normal random variable with mean µ = 3 and variance...
. Suppose that Y is a normal random variable with mean
µ = 3 and variance σ
2 = 1; i.e.,
Y
dist = N(3, 1). Also suppose that X is a binomial random variable
with n = 2 and p = 1/4; i.e.,
X
dist = Bin(2, 1/4). Suppose X and Y are independent random
variables. Find the expected
value of Y
X. Hint: Consider conditioning on the events {X = j} for j = 0, 1,
2.
8....
Let X and Y be two independent Gaussian random variables with common variance σ2. The mean of X i...
Let X and Y be two independent Gaussian random variables with common variance σ2. The mean of X is m and Y is a zero-mean random variable. We define random variable V as V- VX2 +Y2. Show that: 0 <0 Where er cos "du is called the modified Bessel function of the first kind and zero order. The distribution of V is known as the Ricean distribution. Show that, in the special case of m 0, the Ricean distribution simplifies...
11 a12 13 11 021 C11 C12 C13 a31 a32 a33 1)13 123 C31 C32 C33 Assume that Y is a 3 1 random vector with mean vector μΥ- 1-1 and covariance matrix ΣΥΥ-σ2, I. Assume that e is an independent random variable variable with zero mean and variance φ2 4, Derive the mean and variance for W = [1-2 1] . Y +e. 5. Derive the covariance matrix between W and Y 6. Derive the correlation matrix between Wand...
Please explain how to get variance covariance matrix and how to
get the final solution:
ρρ 4. The correlation matrix of the random variables Y,,Y,,Y,, Y4 is 12 3 0 < ρ < l , and each random variable has variance σ2 . Let W1-Y1 +Ý, +Ý, , and let W2 Y +Y +Y,. Find the variance covariance matrix of (W,W2) Jo 1 1 01 L : I :).andi Solution: The matrix M of the linear transformations is M =...
Consider a random vector Y () y(2). y(k) where the elements y(i) are made yi)wi), j-1, ...k where w(j) are independent, identically distributed, Gaussian, zero-mean, and with the variance σ2 i.e., N(0, σ2). 1. Find the Maximum Likelihood (ML) estimator for xr, i.e., ML 2. Find the Mean Square Error (MSE) of ML estimator, i.e., MSE(XML) Ξ Var@sL) 3. Is this estimator consistent? Prove your answer 4. Is this estimator efficient? Prove your answer
2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector,
2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector,
Problem 3: 10 points σ2. Define Assume that U, V, and W are independent random variables with the same common variance X= + W and Y-V-W. 1. Find the variances Var[X] and Var[Y 2. Find the covariance between X and Y, that is: cov [x,Y 3. Find the covariance between (X+Y) and (X - Y), that is: COV[(X +Y), (X -Y)]
Let Y = (Yİ Y2 Yn)' be a random vector taking on values in Rn with mean μ E Rn and covariance matrix 2. Also let 1 be the ones vector defined by 1-(1 1) 5.i Find the projection matrix Hy where V is the subspace generated by 1 5.ii Show that Hy is symmetric and idempotent. 5.iii Let x = (a a . .. a)', where a E Rn. Show that Hvx = x. 5.iv Find the projection of...
Suppose X is a random vector, where X = (X(1), . . . , x(d))T , d with mean 0 and covariance matrix vv1 , for some vector v ER 1point possible (graded) Let v = . (i.e., v is the normalized version of v). What is the variance of v X? (If applicable, enter trans(v) for the transpose v of v, and normv) for the norm |vll of a vector v.) Var (V STANDARD NOTATION SubmitYou have used 0...
. Suppose that Y is a normal random variable with mean
µ = 3 and variance σ
2 = 1; i.e.,
Y
dist = N(3, 1). Also suppose that X is a binomial random variable
with n = 2 and p = 1/4; i.e.,
X
dist = Bin(2, 1/4). Suppose X and Y are independent random
variables. Find the expected
value of Y
X. Hint: Consider conditioning on the events {X = j} for j = 0, 1,
2.
8....
Let X and Y be two independent Gaussian random variables with common variance σ2. The mean of X is m and Y is a zero-mean random variable. We define random variable V as V- VX2 +Y2. Show that: 0 <0 Where er cos "du is called the modified Bessel function of the first kind and zero order. The distribution of V is known as the Ricean distribution. Show that, in the special case of m 0, the Ricean distribution simplifies...
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