2 Let X1, X2, ..., X, be independent continuous random variables from the following distribution: (*)...
2 Let X1, X2, ..., X., be independent continuous random variables from the following distribution: f(x)=ox-(-V where = 1 and a > 1 You may use the fact: E(X)= -1 2.1 Show that the maximum likelihood estimator of a isante = sok X. 2.2 Show that the method moment estimator for a is: & mom = 1 2.3 Derive a sufficient statistic for a. What theorem are you using to determine sufficiency?
2 Let X1, X2, ...,X, be independent continuous random variables from the following distribution: f(3) = ox-(0-1) where : > 1 and a > 1 You may use the fact: E[X]- .- 2.1 Show that the maximum likelihood estimator of a is ômle = Ei log Xi 2.3 Derive a sufficient statistic for a. What theorem are you using to determine sufficiency? 2.4 Show that the fisher information in the whole sample is: 1(a)= 2.5 What Cramer Rao lower bound...
2 Let X1, X2, ..., X, be independent continuous random variables from the following distribution: f(x) = or-(-) where x 2 1 and a > 1 You may use the fact: E[X] - - 2.4 Show that the fisher information in the whole sample is: In(a)= 2.5 What Cramer Rao lower bound for unbiased estimators of a? 2.7 Consider estimating the unknown quantity: g(a) = 0 - 4+.. Determine the MLE of gla). What property are you using to justify...
2 Let X, X2, ..., X, be independent continuous random variables from the following distribution: f(x) - ar"(-) where 2 2 1 and a > 1 You may use the fact: EX- 2.4 Show that the fisher information in the whole sample is: In(a) = 2.5 What Cramer Rao lower bound for unbiased estimators of a? 2.7 Consider estimating the unknown quantity: 9(a) = alet. Determine the MLE of g(a). What property are you using to justify your answer?
Let X1, X2, ..., X, be iid random variables with a "Rayleigh” density having the following pdf: f(x) = 2x2=+*10, 2 > 0 > 0 V лв a) (3 points) Find a sufficient estimator for using the Factorization Theorem. b) (3 points) Find a method of moments estimator for 0. Small help: E(X1) = c) (7 points) What is the MLE of 02 +0 - 10 ? d) (7 points) For a fact, IX has a Gamman, o) distribution. Using...
Let X1, X2, ..., X, be iid random variables with a "Rayleigh" density having the following pdf: f(x) = 6-2°/0, a>0, 0x0 a) (3 points) Find a sufficient estimator for 0 using the Factorization Theorem. b) (3 points) Find a method of moments estimator for 6. Small help: E(X.) = V** c) (7 points) What is the MLE of 02 +0 -10? d) (7 points) For a fact, Li-1 X? has a Gammain,6) distribution. Using this information, find a consistent...
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
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...
Let X1, X2, ..., Xn be iid random variables with a "Rayleigh” density having the following pdf: 22 -12 10 f(x) = e x > 0 > 0 0 пе a) (3 points) Find a sufficient estimator for 0 using the Factorization Theorem. b) (3 points) Find a method of moments estimator for 0. Small help: E(X1) = V c) (7 points) What is the MLE of 02 + 0 – 10 ? d) (7 points) For a fact, 21–1...
QUESTION 3 17) Let Xi. X. X be a random sample from a distribution with probability density function f(x, ?) | ße_ß, for x >0 elsewhere (a) What is the likelihood (LU) = L (x1.X2. xalß)) of the sample? Simplify it. (b) Use the factorization criterion/theorem to show that ? x, is a sufficient statistic for . 4