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 distributio...
8(100) Let X1,,Xn be iid from r(a, 6). (1)(50) Find the limiting distribution of the MLE of B. (2)(30) Find the limiting distribution of the MLE of B when a is known. (3)(20) Compare two asymptotic variances in (1) and (2), and make comment on it. 1ラ 8(100) Let X1,,Xn be iid from r(a, 6). (1)(50) Find the limiting distribution of the MLE of B. (2)(30) Find the limiting distribution of the MLE of B when a is known. (3)(20)...
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.]
4. Let X1, X2, ..., Xn be iid from the Bernoulli distribution with common probability mass function Px(x) = p*(1 – p)1-x for x = 0,1, and 0 < p < 1 14 a. (4) Find the MLE Ôule of p.
Let X1, . . . , Xn ∼ iid Unif(θ − 1/2 , θ + 1/2 ) for θ unknown. Find an asymptotic confidence interval for θ.
Let X1,…, Xn be a sample of iid Bin(1, ?) random variables, and let T = X(1 − X) be an estimator of Var(Xi ) = ?(1 − ?). Determine E(T). Bias(T; ?(1 − ?)).
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 ?
6. Let X1,..., Xn be a random sample from Uniform (0, 1). a) Find the exact distribution of U = – log(X(1)) where X(1) = min(X1, X2,..., Xn). b) Find the limiting distribution of n(1 – X(n)), where X(n) = max(X1, X2, ..., Xn).
Let X1, . . . , Xn ∼ iid Unif(θ − 1/2 , θ + 1/2 ) for θ unknown. Find an asymptotic confidence interval for θ.
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....
Suppose X1, X2, . . . , Xn are iid based on the random variable modeled by where 0 ≤ x ≤ 1 and α > 0. a. Find an equation that the MLE for α must satisfy. Note: You will not be able to explicitly solve for the MLE as in other problems. b. If you are told E(X) = 1/2 and Var(X) = 1/(8α + 4), find the MME for α. This problem is a nice example where...