Again, let X1,..., Xn be iid observations from the Uniform(0,0) distribution. (a) Find the joint pdf...
3. Again, let XXn be iid observations from the Uniform(0,0) distribution. (a) Find the joint pdf of Xo) and X(a) (b) Define R-X(n) - Xu) as the sample range. Find the pdf of R (c) It turns out, if Xi, X, n(iid) Uniform(0,e), E(R)- What happens to E(R) as n increases? Briefly explain in words why this makes sense intuitively.
Only ques 4 (b) Define R = X(n)-X(1) as the sample range. Find the pdf of R. (c) It turns out, if Xi, . . . , Xn ~ (iid) Uniform(0,0), E(R)-θ . What happens to E(R) as n increases? Briefly explain in words why this makes sense intuitively. 4. Let X. Xn be a random sample from a population with pdf xotherwise Let Xa)<..< X(n) be the order statistics. Show that Xa)/X() and X(n) are independent random variables 5....
Ques 3 (d) Suppose that n-10, and Xi Xio represent the waiting times that the 10 people must wait at a bus stop for their bus to arrive. Interpret the result of (c) in the context of this scenario be iid observations from the Uniform(0,0) distribution. 3. Again, let X..., X (a) Find the joint pdf of Xu) and X() (b) Define R = X(n)-X(1) as the sample range. Find the pdf of R. (e) It turns out, if X...
Let X1, ..., Xn be IID observations from Uniform(0, θ). T(X) = max(X1, . . . Xn) is a sufficient statistic (additionally, T is the MLE for θ). Find a (1 − α)-level confidence interval for θ. [Note: The support of this distribution changes depending on the value of θ, so we cannot use Fisher’s approximation for the MLE because not all of the regularity assumptions hold.]
Suppose X1, X2, ..., Xn are independent and identically distributed (iid) with a Uniform -0,0 distri- bution for some unknown e > 0, i.e., the Xi's have pdf Suppose X1, X2,..., Xn are independent and identically distributed (iid f(3) = S 20, if –0 < x < 0; 20 0, otherwise. (a) (4 pts) Briefly explain why or why not this is an exponential family (b) (5 pts) Find one meaningful sufficient statistic for 0. (By "meaningful”, I mean it...
Let X1, X2, ..., Xn be iid random variables from a Uniform(-0,0) distribution, where 8 > 0. Find the MLE of 0.4
Let X1, · · · ,Xn be iid from Uniform(−θ,θ), where θ > 0. Let X(1) < X(2) < ... < X(n) denotes the order statistics. (a) Find a minimal sufficient statistics for θ (d) Find the UMVUE for θ. (e) Find the UMVUE for τ(θ) = P(X1 > k).
Problem 8: 5 points] Let Xi,.,.Xn be IID from a Uniform distribution on (-0,0) where 0 0 is an unknown parameter (a) Find a minimal sufficient statistic T. (b) Define Show that T and V are independent.
Let Xi, , Xn be a sample from U(0,0), θ 0. a. Find the PDF of X(n). b. Use Factorization theorem to show that X(n) is sufficient for θ. C. Use the definition of complete statistic to verify that X(n) is complete for θ.
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.