Let X1, ..., Xn be a random sample from the distribution 1 f(x; 01, 02) e-(2–01)/02...
1. Let X1, ..., Xn be a random sample from a distribution with the pdf le-x/0, x > 0, N = (0,00). (a) Find the maximum likelihood estimator of 0. (b) Find the method of moments estimator of 0. (c) Are the estimators in a) and b) unbiased? (d) What is the variance of the estimators in a) and b)? (e) Suppose the observed sample is 2.26, 0.31, 3.75, 6.92, 9.10, 7.57, 4.79, 1.41, 2.49, 0.59. Find the maximum likelihood...
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).
1. Let X1, ..., Xn be a random sample from a distribution with cumulative dist: 10, <<0 F(x) = (/), 0<x<B | 1, >B > (a) For this part, assume that is known and B is unknown. Find the method of moments estimator Boom of B. (b) For this part, assume that both 6 and B are unknown. Find the maximum likelihood estimators of 8 and B.
Let X1, X2, ..., Xn be a random sample from the distribution with pdf f(3;6) = V porta exp ( 0) 10.02) for some parameter 2 > 0. (a) Find the MLE for 0. (b) Find the Cramér-Rao lower bound for the variance of all unbiased estimators of 0. (c) Find the asymptotic distribution of your MLE from part (a).
Let X1, X2,.. Xn be a random sample from a distribution with probability density function f(z | θ) = (g2 + θ) 2,0-1(1-2), 0<x<1.0>0 obtain a method of moments estimator for θ, θ. Calculate an estimate using this estimator when x! = 0.50. r2 = 0.75, хз = 0.85, x4= 0.25.
Let X1 Xn be a random sample from a distribution with the pdf f(x(9) = θ(1 +0)-r(0-1) (1-2), 0 < x < 1, θ > 0. the estimator T-4 is a method of moments estimator for θ. It can be shown that the asymptotic distribution of T is Normal with ETT θ and Var(T) 0042)2 Apply the integral transform method (provide an equation that should be solved to obtain random observations from the distribution) to generate a sam ple of...
1. [8 points] Suppose Xi... Xn is a random sample from a Pareto distribution with the density If x > 1 otherwise, where ? > 1, Find the method of moments estimator of ?.
Let X1, X2, ..., Xn be a random sample from the distribution with probability density function f(x;t) = Botha, 0 < x < 2, t> -4. a. Find the method of moments estimator of t, t . Enter a formula below. Use * for multiplication, / for division and ^ for power. Use m1 for the sample mean X. For example, 7*n^2*m1/6 means 7n27/6. ſ = * Tries 0/10 b. Suppose n=5, and x1=0.36, X2=0.96, X3=1.16, X4=1.36, X5=1.96. Find the...
6.4.3. Let X1, X2, ..., Xn be iid, each with the distribution having pdf f(x; 01, 02) = (1/02)e-(2–01)/02, 01 < x <ao, -20 < 02 < 0o, zero elsewhere. Find the maximum likelihood estimators of 01 and 02.
1 Let X1,..., Xn be iid with PDF x/e f(x;0) ',X>0 o (a) Find the method of moments estimator of e. (b) Find the maximum likelihood estimator of O (c) Is the maximum likelihood estimator of efficient?