0 2.2.8. Suppose X1 and X2 have the joint pdf I e-le-22 21 > 0, X2...
1. Let X1 and X2 have the joint pdf f(x1, x2) = 2e-11-22, 0 < 11 < 1 2 < 0o, zero elsewhere. Find the joint pdf of Yı = 2X1 and Y2 = X2 – Xı.
Let X1 and X2 have joint PDF f(x1,x2)=x1+x2 for 0 <x1 <1 and 0<x2 <1.(a) Find the covariance and correlation of X1 and X2. (b) Find the conditional mean and conditional variance of X1 given X2 = x2.
Suppose that X1 and X2 have joint PDF xx2(,2)o 0 : otherwise (a) Use the transformation technique to find the joint PDF of Yǐ and Ý, where Yi = X1/X2 and Y2-X2 (b) Using your answer to part (a), find and identify the distribution of Yi
Power function
sample with joint pdf (or pmf) f (x |0), 0 e 0 c R. Suppose Let X1,..., X,n be a that {f(xn0) : 0 E 0} has monotone likelihood ratio (MLR) in T(X). Consider test function if T(xn)> c 1 if T(Xn) (Xn) C if T(xn)c 0 where y E [0, 1] and c > 0 are constants. Prove that the power function of ø(X,,) is non-decreasing in 0
sample with joint pdf (or pmf) f (x |0),...
3. Let X1,..Xn be a sample with joint pdf (or pmf) f(x,0), 0 e 0 c R. Suppose that {f(x, 0) 0 e 0} has monotone likelihood ratio (MLR) in T(X,). Consider test function if T(xn)> c if T(xn) c if T(x)<c 0 E [0,1 and c 2 0 are constants. Prove that the power function of ¢(X,) is where non-decreasing in 0
3. Let X1,..Xn be a sample with joint pdf (or pmf) f(x,0), 0 e 0 c R....
Suppose that X1, X2, .., Xn are iid Poisson observations, each having common pdf 0 e-8 0, otherwise. Find the UMVUE of τ(0)-g2.
Suppose X1, X2, . . . , Xn are iid with pdf f(x|θ) = θx^(θ−1) I(0 ≤ x ≤ 1), θ > 0. (a) Is − log(X1) unbiased for θ^(−1)? (b) Find a better estimator than log(X1) in the sense of with smaller MSE. (c) Is your estimator in part (b) UMVUE? Explain.
The random variables X1, X2, - .. are independent and identically distributed with common pdf 0 х > fx (x;0) (2) ; х<0. This distribution has many applications in engineering, and is known as the Rayleigh distribution. 2 (a) Show that if X has pdf given by (2), then Y = X2/0 is x2, i.e. T (1, 2) i.e. exponential with mean 2, with pdf fr (y;0) - ; y0; (b) Show that the maximum likelihood estimator of 0 is...
Let X1,X be a random sample from an EXP(0) distribution (0 > 0) You will use the following facts for this question: Fact 1: If X EXP(0) then 2X/0~x(2). Fact 2: If V V, are a random sample from a x2(k) distribution then V V (nk) (a) Suppose that we wish to test Ho : 0 against H : 0 = 0, where 01 is specified and 0, > Oo. Show that the likelihood ratio statistic AE, O0,0)f(E)/ f (x;0,)...
Let (X,Y) have joint pdf given by I c, \y < x, 0 < x < 1, f(x, y) = { | 0, 0.W., (a) Find the constant c. (b) Find fx(r) and fy(y) (c) For 0 < x < 1, find fy\X=z(y) and HY|X=r and oſ X=z- (d) Find Cov(X, Y). (e) Are X and Y independent? Explain why.