6. Let fxy(x, y) = 10 (x,y) where D is the region of R2 shown below....
Section 6.5: Mean Square Estimation 6.68. Let X and Y be discrete random variables with three possible joint pmf's: Let X and Y have joint pdf: fx.y(x, y) -k(x + y) for 0 sxs 1,0s ys1 Find the minimum mean square error linear estimator for Y given X. Find the minimum mean square error estimator for Y given X. Find the MAP and ML estimators for Y given X. Compare the mean square error of the estimators in parts a,...
Let D be the region bounded by x + y2 = 1 and x+y=1 in R2. Find the volume of the solid under the plane 2x + y – z= -1 and above the region D.
(a) Sketch the region in the (x,y) plane where ??,?(?, ?) ≠
0.
(b) Find the marginal probability density functions ??(?) and
??(?) of ? and ? respectively.
(c) Are X and Y independent?
(d) Find P(Y>X).
(e) Let y be some real number in the range 0 ≤ y ≤ 1. Find the
conditional probability density function ??|?(?|?).
(f) Find ?[?|? = ?] (where ? is some real number in the range 0
≤ ? ≤ 1).
The joint...
1. The joint probability density function (pdf) of X and Y is given by fxy(x, y) = A (1 – xey, 0<x<1,0 < y < 0 (a) Find the constant A. (b) Find the marginal pdfs of X and Y. (c) Find E(X) and E(Y). (d) Find E(XY). 2. Let X denote the number of times (1, 2, or 3 times) a certain machine malfunctions on any given day. Let Y denote the number of times (1, 2, or 3...
Please explain step by step, especially option b.
1. Continuous random variables X and Y have a joint PDF given by fxy(x, y) = 2/3 if (2, y) belongs to the closed shaded region O otherwise We want to estimate Y based on X. (a) Find the LMS estimator g(x) of Y. (b) Calculate the conditional mean squared error E ((Y – g(x))| X = 2). (c) Calculate the mean squared error E (Y - g(x))?). Is it the same...
Thejoint PDFofabivariate RV (X,Y ) is given by fXY (x,y)= where k isaconstant. (a) Determine the value of k. (b) Find themarginal PDFsof X andY. (c) Find P(0<X <1/2,0<Y <1/2). (d) Findtheconditional PDFs fY|X(y|x) and fX|Y (x|y). (e) Computetheconditional meansE[Y |x] andE[X|y]. (f) Computetheconditional variancesVar(Y |x) andVar(X|y). otherwise { k, 0<y≤x<1, 0, otherwise, Thejoint PDFofabivariate RV (X,Y ) is given by fXY (x,y)= { k, 0<y≤x<1, 0, otherwise, where k isaconstant. (a) Determine the value of k. (b) Find themarginal...
1) Let X and Y have joint pdf: fxy(x,y) = kx(1 – x)y for 0 < x < 1,0 < y< 1 a) Find k. b) Find the joint cdf of X and Y. c) Find the marginal pdf of X and Y. d) Find P(Y < VX) and P(X<Y). e) Find the correlation E(XY) and the covariance COV(X,Y) of X and Y. f) Determine whether X and Y are independent, orthogonal or uncorrelated.
Let the random variables X, Y with joint probability density function (pdf) fxy(z, y) = cry, where 0 < y < z < 2. (a) Find the value of c that makes fx.y (a, y) a valid pdf. (b) Calculate the marginal density functions for X and Y (c) Find the conditional density function of Y X (d) Calculate E(X) and EYIX) (e Show whether X. Y are independent or not.
5. Let the joint density of X and Y be fr(x,) = (x + y, fxy(x, y) = 0, 0<x< 1,0 <y <1 otherwise (a) Find the marginal pdfs of X and Y. (b) Are X and Y independent? (c) Are X and Y correlated? (d) Find P(X + Y < 1).
( xy 7. CHALLENGE: fxy(x, y) = 0< < 2, 0 <y <1 otherwise 0 Find P(X+Y < 1) HINT: consider the region of the XY plane where the inequality is true.