a) MLE :
b) Fisher Information :
c) MLE of is
Fisher information I() = 1 / Var(MLE) = 1 / Var() = 1 / (/n) = n/
d) Confidence Interval for the parameter :
Question 3: Let X1,..., X.be iid Poisson (2) random variables. a. Find the maximum likelihood estimate...
Suppose that X1,X2,. X are iid random variables with pdf ,220 (a) Find the maximum likelihood estimate of the parameter a (b) Find the Fisher Information of X1,X2,.. ., Xn and use it to estimate a 95% confidence interval on the MLE of a (c) Explain how the central limit theorem relates to (b).
Suppose that Xi, X2Xn are iid random variables with pdf eter a. (b) Find the Fisher Information of X1,X2, ,Xn and use it to estimate a 95% confidence interval on the MLE of a. (c) Explain how the central limit theorem relates to (b).
Let X1, · · · , X20 be independent Poisson random variables with mean (print please) 1. (i) Use the pmf of Poisson distribution to compute P(X1 + · · · + X20 > 15). (ii) Use the Markov inequality to obtain a bound on P(X1 + · · · + X20 > 15). (iii) Use the central limit theorem to approximate P(X1 + · · · + X20 > 15).
Let X1, ..., X20 be independent Poisson random variables with mean one. 1 2 (a) Use the Markov inequality to obtain a bound on P (X1 + X2 + · · · + X20 > 15). (b) Use the central limit theorem to approximate the above probability.
Let X1, …, Xn be iid Poisson(λ). Find the maximum likelihood estimator λMLE for λ, when it is given that λ > λ*, where λ* > 0 is a fixed constant. (Note: This is asking you to find the restricted MLE)
Question 2 Let X1,...,X, be iid Geometric random variables with parameter and probability mass function f(T; 7) = (1 - 7)" for 1 = 0,1,2,... and 0 <I<1. We wish to test: HT=0.50 HT70.50 (a) Find the three asymptotic x1) test statistics (Likelihood Ratio, Wald, and Score) for this setting. versus
Let X1,X2,...,Xn be iid exponential random variables with unknown mean β. (b) Find the maximum likelihood estimator of β. (c) Determine whether the maximum likelihood estimator is unbiased for β. (d) Find the mean squared error of the maximum likelihood estimator of β. (e) Find the Cramer-Rao lower bound for the variances of unbiased estimators of β. (f) What is the UMVUE (uniformly minimum variance unbiased estimator) of β? What is your reason? (g) Determine the asymptotic distribution of the...
Suppose that (X1, X2,,,,Xn) are iid random variables. Find the maximum likelihood estimator of theta for the following distributions 1) Poi(theta) 2) N(Mu, theta) 3) Exp(theta)
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....
3. [20 marks] Consider the multinomial distribution with 3 categories, where the random variables Xi, X2 and X3 have the joint probability function where x = (zi, 2 2:23), θ = (θί, θ2), n = x1 + 2 2 + x3, θι, θ2 > 0 and 1-0,-26, > 0. (a) [4 marks] Find the maximum likelihood estimator θ of θ. (b) [4 marks] Find that the Fisher information matrix I(0) (c) [4 marks] Show that θ is an MVUE. (d)...