Let Xi iid∼ N(0, θ) for i = 1, ..., n.
a) Find the MLE for θ. Call it
b) Is biased?
c) Is consistent?
d) Find the variance of
(e) What is the asymptotic distribution of ?
4. Xi ,i = 1, , n are iid N(μ, σ2). (a) Find the MLE of μ, σ2. Are these unbiased estimators of μ and of σ2 respectively? Aside: You can use your result in (b) to justify your answer for the bias part of the MLE estimator of σ2 (b) In this part you will show, despite that the sample variance is an unbiased estimator of σ2, that the sample standard deviation is is a biased estimator of σ....
4. Let Xi" pois(1) for i = 1, ..., n. (a) Find the MLE for d. Call it û (b) What is the asymptotic distribution of î? (c) Find an estimator for P(X1 < 1) (hint: write down P(X1 < 1) using the distribution. Can you use a property of MLEs to get this? )
Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1 where I(.) denotes the indicator function. (a) Find a 2-dimensional sufficient statistic for the mode (b) Suppose θ is a known constant. Find the MLE for v. (d) Suppose v-1. Find the MLE for and determine its asymptotic distribution. Carefully justify your answer and state any theorems that you use. (e) Suppose1. Find the asymptotic distribution of the MLE estimator of exp[- Let Xi,... ,Xn be i.i.d with pdf θνθ θ+1...
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0. In the last homework, you have computed the maximum likelihood estimator θ for θ in terms of the sample averages of the linear and quadratic means, i.e. Xn and X,and applied the CLT and delta method to find its asymptotic variance. In this problem, you will compute the asymptotic variance of θ via the Fisher Information....
Let Xi , X2,. … X, denote a random sample of size n > 1 from a distribution with pdf f(x:0)--x'e®, x > 0 and θ > 0. a. Find the MLE for 0 b. Is the MLE unbiased? Show your steps. c. Find a complete sufficient statistic for 0. d. Find the UMVUE for θ. Make sure you indicate how you know it is the UMVUE. Let Xi , X2,. … X, denote a random sample of size n...
4.(120) Let X1,,,Xn be iid r(, 1) and g(u) given. Let 6n be the MLE of g(4) (1)(60) Find the asymptotic distribution of 6, (2)(60) Find the ARE of T Icc(X) w.r.t. on P(X1> c), c > 0 is i n i1 5.(80) Let X1, ,,Xn be iid with E(X1) = u and Var(X1) limiting distribution of nlog (1 +). o2. Find the where T n(X - 4)/s. - 1 - 4.(120) Let X1,,,Xn be iid r(, 1) and g(u)...
please solve 6 4. Let Xi. X2. . Xnbe ap (1 I: 1 Xi ) 1/n is a consistent estimator for θ e . BAN. [Show that n(θ-X(n)) G (1, θ the estimator T0(X) = (n + 2)X(n)/(n + 1) in this class has the least MSE. an 5. In Problem 2, show that TX)Xm) is asymptotically biased for o 6.In Problem 5, consider the class of estimators T(X) cX(n), c 0. Sho 4. Let Xi. X2. . Xnbe ap...
Let X1, X2, ..., Xn be iid with pdf f(x|θ) = θ*x(θ-1). a) Find the Maximum Likelihood Estimator of θ, and b) show that its variance converges to 0 as n approaches infinity. I have no problem with part a, finding the MLE of θ. However, I'm having some trouble with finding the variance. The professor walked us through part b generally, but I need help with univariate transformation for sigma(-ln(xi)) (see picture below - the professor used Y=sigma(-ln(x)), and...
Let Xi iid∼ Unif(0, θ) for i = 1, 2, 3 and = 4Y(1) = 2Y(2) θ* = (4/3)Y(3) (a) For each estimator compute the bias? (b) For each estimator compute the variance? (c) Which estimator is best and why?
1.(c) 2.(a),(b) 5. Let Xi,..., X, be iid N(e, 1). (a) Show that X is a complete sufficient statistic. (b) Show that the UMVUE of θ 2 is X2-1/n x"-'e-x/θ , x > 0.0 > 0 6. Let Xi, ,Xn be i.i.d. gamma(α,6) where α > l is known. ( f(x) Γ(α)θα (a) Show that Σ X, is complete and sufficient for θ (b) Find ElI/X] (c) Find the UMVUE of 1/0 -e λ , X > 0 2) (x...