


![.: Elget] = 0 Hence get) = ant! is UMVUE of 6 * ** Thanking you -](http://img.homeworklib.com/questions/23a4d370-95b6-11eb-ada0-cdb31cb54e8d.png?x-oss-process=image/resize,w_560)
Q. 4 Let X1, ... , Xn be a random sample from gamma (2,0) distribution. c)...
May 21, 2019 R 3+3+5-11 points) (a) Let X1,X2, . . Xn be a random sample from G distribution. Show that T(Xi, . . . , x,)-IT-i xi is a sufficient statistic for a (Justify your work). (b) Is Uniform(0,0) a complete family? Explain why or why not (Justify your work) (c) Let X1, X2, . .., Xn denote a random sample of size n >1 from Exponential(A). Prove that (n - 1)/1X, is the MVUE of A. (Show steps.)....
Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = (1/θ)e^(−x/θ) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ. Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = θe^(−θx) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ.
Let X1, X2, ..., Xn be a random sample from a Gamma( a , ) distribution. That is, f(x;a,0) = loga xa-le-210, 0 < x <co, a>0,0 > 0. Suppose a is known. a. Obtain a method of moments estimator of 0, 0. b. Obtain the maximum likelihood estimator of 0, 0. c. Is O an unbiased estimator for 0 ? Justify your answer. "Hint": E(X) = p. d. Find Var(ë). "Hint": Var(X) = o/n. e. Find MSE(Ô).
4. Let X1, X2, ...,Xn be a random sample from a normal distribution with mean 0 and unknown variance o2. (a) Show that U = <!-, X} is a sufficient statistic for o?. [4] (c) Show that the MLE of o2 is Ô = 2-1 X?. [4] (c) Calculate the mean and variance of Ô from (b). Explain why ő is also the MVUE of o2. [6]
Let X1 ,……, Xn be a random sample from a Gamma(α,β) distribution, α> 0; β> 0. Show that T = (∑n i=1 Xi, ∏ n i=1 Xi) is complete and sufficient for (α, β).
7.6.4. Let X1, X2,... , Xn be a random sample from a uniform (0,) distribution. Continuing with Example 7.6.2, find the MVUEs for the following functions of (a) g(0)-?2, i.e., the variance of the distribution (b) g(0)- , i.e., the pdf of the distribution C) or t real, g(9)- , î.?., the mgf of the distribution. Example 7.6.2. Suppose X1, X2,... , Xn are iid random variables with the com- mon uniform (0,0) distribution. Let Yn - max{X1, X2,... ,...
Let X1, ..., Xn be a random sample from Gamma(1,41) distribution and Y1, ..., Ym be a random sample from Gamma(1,12) distribution. Also assume that X’s are independent of Y's. (1) Formulate the LRT for testing Ho : 11 = 12 v.s. Hy : 11 + 12; (10 points) (2) Show that the test in part (1) can be based on the following statistic (7 points) T = 21-1 Xi Dizi Xi + [2Y; = (3) Find the distribution of...
Let X1, . . . , Xn be a random sample from the uniform distribution on the interval (θ, θ + 1), θ > 0. Find a sufficient statistic for θ.
Let X1, . . . , Xn be a random sample from the discrete uniform distribution on 1, 2, . . . , θ. Using the definition of sufficient statistic, show that X(n) is a sufficient statistic for θ.
4. Let X1, X2, ..., Xn be a random sample from an Exponential(1) distribution. (a) Find the pdf of the kth order statistic, Y = X(k). (b) Determine the distribution of U = e-Y.