have a Ba- Question 2. (20 points) Let (X1,...,xn) be a sample from Poisson(2), and let...
Let X1, . . . , Xn be a random sample following Gamma(2, β) for some unknown parameter β > 0. (i) Now let’s think like a Bayesian. Consider a prior distribution of β ∼ Gamma(a, b) for some a, b > 0. Derive the posterior distribution of β given (X1, . . . , Xn) = (x1,...,xn). (j) What is the posterior Bayes estimator of β assuming squared error loss?
3. Let Xi, , Xn be a random sample from a Poisson distribution with p.m.f Assume the prior distribution of Of λ is is an exponential with mean 1, i.e. the prior pdi g(A) e-λ, λ > 0 Note that the exponential distribution is a special gamma distribution; and a general gamma distribution with parameters α > 0 and β > 0 has the pd.f. h(A; α, β)-16(. otherwise Also the mean of a gamma random variable with the pd.f.h(Χα,...
[4] (15 pts) Let X1, ... , Xn (n > 2) be a random sample from a Poisson distribution with unknown mean 8 >0. Find the UMVUE of n = P(X1 > 1) = 1 - - (5) (30 pts ; 15 pts each) (a) Let X1,.,X, be a random sample from a Pareto distribution, Pareto(a,1), with pdf f(x; a) = 0x ax-(+1)I(1,00)() where a > 0 is unknown. Find the UMVUE of n = P. (X1 > c) =...
Let X1, ..., Xn be a random sample from Gamma(1,41) distribution and Y1, ..., Ym be a random sample from Gamma(1,12) distribution. Also assume that X’s are independent of Y's. (1) Formulate the LRT for testing Ho : 11 = 12 v.s. Hy : 11 + 12; (10 points) (2) Show that the test in part (1) can be based on the following statistic (7 points) T = 21-1 Xi Dizi Xi + [2Y; = (3) Find the distribution of...
5. Let X1, X2, ..., Xn be a random sample from a distribution with pdf of f(x) = (@+1)xº,0<x<1. a. What is the moment estimator for 0 using the method of moments technique? b. What is the MLE for @ ?
Let Xi , i = 1, · · · , n be a random sample from Poisson(θ) with pdf f(x|θ) = e −θ θ x x! , x = 0, 1, 2, · · · . (a) Find the posterior distribution for θ when the prior is an exponential distribution with mean 1; (b) Find the Bayesian estimator under the square loss function. (c) Find a 95% credible interval for the parameter θ for the sample x1 = 2, x2...
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 denote an independent random sample from a population with a Poisson distribution with mean . Derive the most powerful test for testing Ho : 1= 2 versus Ha: 1= 1/2.
3. Let X1 , X2, . . . , Xn be a randon sample from the distribution with pdf f(r;0) = (1/2)e-z-8,-X < < oo,-oc < θ < oo. Find the maximum likelihood estimator of θ.
Let X1,..., Xn be a random sample from the pdf f(x:0)-82-2, 0 < θ x < oo. (a) Find the method of moments estimator of θ. (b) Find the maxinum likelihood estimator of θ