Suppose that X1, X2,., Xn is an iid sample from the probability mass function (pmf) given...
Suppose X1, X2, , xn is an iid sample from fx(x10)-θe_&z1 (a) For n 2 2, show that (x > 0), where θ > 0 . n- is the uniformly minimum variance unbiased estimator (UMVUE) of θ (b) Calculate varo(0). Comment, in particular, on the n 2 case. (c) Show that vars(0) does not attain the Cramer-Rao Lower Bound (CRLB) on the variance of all unbiased estimators of T(9-0 (d) For this part only, suppose that n 1, 11T(X) is...
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 X1, X2, ..., Xn is an iid sample from fx(r ja-θ(1-z)0-11(0 1), where x θ>0. (a) Find the method of moments (MOM) estimator of θ. (b) Find the maximum likelihood estimator (MLE) of θ (c) Find the MLE of Po(X 1/2) d) Is there a function of θ, say T 0), for which there exists an unbiased estimator whose variance attains the Cramér-Rao Lower Bound? If so, find it and identify the corresponding estimator. If not, show why not.
Advanced Statistics, I need help with (c) and (d) 2. Let X1, X2, ..., Xn be a random sample from a Bernoulli(6) distribution with prob- ability function Note that, for a random variable X with a Bernoulli(8) distribution, E [X] var [X] = θ(1-0) θ and (a) Obtain the log-likelihood function, L(0), and hence show that the maximum likelihood estimator of θ is 7l i= I (b) Show that dE (0) (c) Calculate the expected information T(e) EI()] (d) Show...
Suppose X1, X2, , Xn is an iid sample from a uniform distribution over (θ, θΗθ!), where (a) Find the method of moments estimator of θ (b) Find the maximum likelihood estimator (MLE) of θ. (c) Is the MLE of θ a consistent estimator of θ? Explain.
7. Let X1,....Xn random sample from a Bernoulli distribution with parameter p. A random variable X with Bernoulli distribution has a probability mass function (pmf) of with E(X) = p and Var(X) = p(1-p). (a) Find the method of moments (MOM) estimator of p. (b) Find a sufficient statistic for p. (Hint: Be careful when you write the joint pmf. Don't forget to sum the whole power of each term, that is, for the second term you will have (1...
Suppose that X1, X2, ,Xn is an iid sample from Íx (x10), where θ Ε Θ. In each case below, find (i) the method of moments estimator of θ, (ii) the maximum likelihood estimator of θ, and (iii) the uniformly minimum variance unbiased estimator (UMVUE) of T(9) 0. exp fx (x10) 1(0 < x < 20), Θ-10 : θ 0}, τ(0) arbitrary, differentiable 20 (d) n-1 (sample size of n-1 only) ー29 In part (d), comment on whether the UMVUE...
Let X1, . . . , Xn be a random sample from a population X with p.d.f fθ(x) = θ xθ−1 , for 0 < x < 1 0, otherwise, where θ > 1 is parameter. Find the MLE of 1/θ. If it is an unbiased estimator of 1/θ, compare its variance with the Cramer-Rao lower bound.
1. Let Xi,..., Xn be a random sample from a distribution with p.d.f. f(x:0)-829-1 , 0 < x < 1. where θ > 0. (a) Find a sufficient statistic Y for θ. (b) Show that the maximum likelihood estimator θ is a function of Y. (c) Determine the Rao-Cramér lower bound for the variance of unbiased estimators 12) Of θ
Suppose that X1, X2,....Xn is an iid sample of size n from a Pareto pdf of the form 0-1) otherwise, where θ > 0. (a) Find θ the method of moments (MOM) estimator for θ For what values of θ does θ exist? Why? (b) Find θ, the maximum likelihood estimator (MLE) for θ. (c) Show explicitly that the MLE depends on the sufficient statistic for this Pareto family but that the MOM estimator does not