Asked by Anonymous
As in an earlier exercise, we assume that the random variables Θ and X are described by a joint PDF which is uniform on the triangular set defined by the constraints 0≤x≤1 , 0≤θ≤x .
a) Find an expression for the conditional mean squared error of the LMS estimator given that X=x , valid for x∈[0,1] . Express your answer in terms of x using standard notation.
a) Find an expression for the conditional mean squared error of the LMS estimator given that X=x , valid for x∈[0,1] . Express your answer in terms of x using standard notation.
Answers
Answered by
Anonymous
a) the conditional PDF of Θ is uniform on the range [0,x] . Hence, the conditional variance is x2/12
b)This is given by the integral of the conditional variance, weighted by the PDF of X . The PDF of X is found using the formula for going from the joint to the marginal, and is fX(x)=2x , for x∈[0,1] . Thus, the mean squared error is
∫10x212⋅2xdx=16∫10x3dx=124.
b)This is given by the integral of the conditional variance, weighted by the PDF of X . The PDF of X is found using the formula for going from the joint to the marginal, and is fX(x)=2x , for x∈[0,1] . Thus, the mean squared error is
∫10x212⋅2xdx=16∫10x3dx=124.
Answered by
Anonymous
The b part is 1/24. Please take note. Thank you for the answer
Answered by
Anonymous
I know to get from the joint to the marginal we integrate, but what is the joint?
Answered by
Anonymous
Part a: (x^2)/12
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