Consider the Pareto distribution
Consider the Pareto distribution Problem 6. Consider the Pareto distribution (BOB 78+1 f(x) = x =...
IV. Let X be a random variable with the following pdf: f() = (a + 1)2 for 0<< 1 0 elsewhere Find the maximum likelihood estimator of a, based on a random sample of size n. Check if the Maximum Likelihood Estimator in Part (a) is unbiased
1. Let Xi...., X, be a random sample from a distribution with pdf f(x;0) = 030-11(0 < x < 1), where 0 > 0. Find the maximum likelihood estimator of u = 8/1 b) Find a sufficient statistic and check completeness. (c) Find the UMVUE(uniformly minimum variance unbiased estimator of each of the following : 0,1/0,4 = 0/(1+0).
1. Let Xi...., X, be a random sample from a distribution with pdf f(x;0) = 030-11(0 < x < 1), where 0 > 0. Find the maximum likelihood estimator of u = 8/1 b) Find a sufficient statistic and check completeness. (c) Find the UMVUE(uniformly minimum variance unbiased estimator of each of the following : 0,1/0,4 = 0/(1+0).
The Pareto probability distribution has many applications in economics, biology, and physics. Let β> 0 and δ> 0 be the population parameters, and let XI, X2, , Xn be a random sample from the distribution with probability density function zero otherwise. Suppose B is known Recall: a method of moments estimator of δ is δ = the maximum likelihood estimator of δ is δ In In X-in β has an Exponential (0--) distribution Suppose S is known Recall Fx(x) =...
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
Likelihood. Let X,,..., X, be an i.i.d. sample from a distribution with density function f(x, Ø) = {eif x > 0, if x <0 (2x Tif x >0 f(x, 0) = {0 where 0 > 0 is an unknown parameter. 1. Use method of maximum likelihood to find the estimator for 0. 2. Apply this formula to estimate 0 from the sample (0.5, 0.5, 1).
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
- ACUJU 1. (6%) Let X be a random variable with probability distribution (1+x **,-1<x< 1 0, elsewhere Find the probability distribution of the random variable Y = X2.
PROBLEM 3 Let X1, X2,L , X, be iid observations from a distribution with pdf given by f(xl0)=0x0-, 0<x<1, 0<O<00. a) Find the maximum likelihood estimator of O. b) Find the moment estimator of 0. c) (Extra credit) Compare the mean squared error of the two estimators in (a) and (b). Which one is better? (5 points)
1. Let X1, ..., Xn be a random sample from a distribution with cumulative dist: 10, <<0 F(x) = (/), 0<x<B | 1, >B > (a) For this part, assume that is known and B is unknown. Find the method of moments estimator Boom of B. (b) For this part, assume that both 6 and B are unknown. Find the maximum likelihood estimators of 8 and B.