Let X1, ..., Xn and Y1, ...,Ym be two independent samples from a Poisson dis- tribution...
Let X1, ..., Xn and Y1, ..., Ym be two independent samples from a Poisson dis- tribution with parameter 1. Let a, b be two positive numbers. Consider the following estimator for 1: i ,Y1 +...+Ym = a- X1 +...+Xn n т (a) What condition is needed on a and b so that û is unbiased? (b) What is the MSE of i?
Let X1,..., Xn and Yi,..., Ym be two independent samples from a Poisson dis- tribution with parameter X. Let a, b be two positive numbers. Consider the following estimator for A: Y1 X1 Xn . Ym b n m (a) What condition is needed on a and b so that X is unbiased? (b) What is the MSE of A?
Given two independent random samples X1, ..., Xn and Y1, ..., Ym with normal dis- tributions N(Hz, o?) and N(Hy, oz), determine a generalized likelihood ratio test for Ho : Mix - My = 0 versus H : plz – My 70 at a given significance level a (01, 0y unknown but equal).
3. Let X1, X2, . . . , Xn be independent samples of a random variable with the probability density function (PDF): fX(x) = θ(x − 1/ 2 ) + 1, 0 ≤ x ≤ 1 ,0 otherwise where θ ∈ [−2, 2] is an unknown parameter. We define the estimator ˆθn = 12X − 6 to estimate θ. (a) Is ˆθn an unbiased estimator of θ? (b) Is ˆθn a consistent estimator of θ? (c) Find the mean squared...
Let X1, . . . , Xn be independent Poisson(θ) random variables with parameter θ > 0. (1) Find the Bayes estimator of θ for a Gamma(α, β) prior. (2) Find the MSE of the Bayes estimator.
Let X1, . . . , Xn be i.i.d. from N(µ1, σ2 ), and Y1, . . . , Ym be i.i.d. from N(µ2, σ2 ). If the two samples are independent, find the maximum likelihood estimates for µ1, µ2, and the common variance σ 2 .
3. Suppose that we have two independent random samples: X1, Xn are exponential(), and Y1,... . Ym are μ. You do not need to find the critical value of exponential(μ). Find the LRT of H0 : θ the test. μ versus Ha : θ
Let X1, X2,..., Xn be a random sample from Poisson(0), 0 > 0. X. Determine the value of a constant c such that the (b) Let Y =1 -0 unbiased estimator of e. estimator eCYis an (c) Get the lower bound for the variance of the unbiased estimator found in (b) Let X1, X2,..., Xn be a random sample from Poisson(0), 0 > 0. X. Determine the value of a constant c such that the (b) Let Y =1 -0...
Let X1, . . . , Xn ∼ iid Exp(λ) and Y1, . . . , Ym ∼ iid Exp(τ ) be independent random samples. (a) Find the restricted MLEs under the null hypothesis H0 : λ = τ . (b) Write out a formula for the LRT statistic, and describe how you could perform this test asymptotically.
Suppose X1,. , Xn are iid Poisson(A) random variables. Show by direct calculation without using any theoremm in mathematical statistics, that (a) Ση! Xi/n is an unbiased estimator for λ. (b) X is optimal in MSE among all unbiased estimators. This is to say, let T be another unbiased estimator, then EA(X) EA(T2